Comprehensive Evaluation Method Research Articles

Research on Partner Selection in Enterprise Innovation Ecosystem

In the face of fierce market competition, enterprises must ensure the competitiveness of their products or services through technological innovation. However, the complexity of technology often surpasses the capabilities of individual enterprises, leading them to deepen cooperation with other organizations. The entities within the enterprise innovation ecosystem depend on each other, collaborate closely, and rely on core enterprises to integrate resources, thereby creating system value and enhancing competitiveness. The purpose of this paper is to explore the process of selecting appropriate ecosystem partners. It begins by providing an overview of relevant concepts, characteristics, selection factors, and methods. Subsequently, it analyzes the roles, resources, and synergy evolution of the entities within the ecosystem. An evaluation system encompassing operation, core, synergy, and development capability is then established. This system comprises 16 indicators, including organization scale and reputation, and is accompanied by a hierarchical evaluation model. Finally, the validity of the evaluation system is confirmed through empirical analysis, utilizing the Analytic Hierarchy Process (AHP) and the fuzzy comprehensive evaluation method.

Spatiotemporal Patterns and Coupling Coordination Analysis of Multiscale Social–Economic–Ecological Effects in Ecologically Vulnerable Areas Based on Multi-Source Data: A Case Study of the Tuha Region, Xinjiang Province

Ecologically fragile areas are confronted with the contradiction between economic development and ecological protection, especially in the Tuha region (Turpan and Hami), where the extremely vulnerable ecological environment limits local sustainable development. To address this, this study utilizes POI (Point of Interest) data, land use, and socioeconomic statistical data to achieve spatial quantification of indicators on a kilometer grid scale, constructing a multi-factor, multi-dimensional evaluation system for the socioeconomic and ecological effects of sustainable development based on SDGs (Sustainable Development Goals). The entropy method, comprehensive evaluation method, coupling coordination degree model, and geographical detector method are used to analyze the coupling relationships between systems at different scales and the factors influencing the system’s coupling coordination degree. The results indicate that from 2010 to 2020, the economic, social, and ecological systems of the Tuha region, as well as their comprehensive scores, exhibited spatial similarity. The economic system showed an upward trend, the social system displayed an inverted U-shaped trend of rising then declining, while the ecological system presented a U-shaped trend of declining then increasing. At the county scale, the coupling coordination degree closely approximates the trend of the comprehensive coordination index, showing a continuous upward trajectory. Compared with Turpan city, Hami city, especially Yizhou district, exhibits the best development in coupling coordination degree, while the growth in coupling coordination degree is most significant in Gaochang district. The main factors influencing the degree of coupling coordination are grain production and GDP (gross domestic product). This study provides a new perspective on the quantification of sustainable development indicators, which is of great significance for balancing economic and social development with ecological protection and promoting the coupled and coordinated development of society, economy, and ecology in ecologically fragile areas.

Enhancing radial strain uniformity of thin-walled cylinder by the dual asymmetric active counter-roller spinning process

Aiming at the problem of uneven forces on the inner and outer surfaces during counter-roller spinning (CRS) of thin-walled cylinders, which affects the spinning stability and forming quality, a new dual asymmetric active counter-roller spinning (DAACRS) process is proposed. It enhances the radial strain uniformity through more consistent contact of the inner and outer rollers and the material flow on the inner and outer surfaces. The theoretical analytical model of the influence of the spinning structural and process parameters on the contact condition and the oriented relationship is established. On this basis, the Kriging predictive surrogate model under the coupling influence of these parameters is established, and the spinning parameters optimized by the multi-objective particle swarm optimization (MOPSO) algorithm in the global continuous variables are obtained. The radial strain gradient effect of traditional spun parts is basically eliminated under this process parameters. Additionally, an active counter-roller spinning (ACRS) machine is independently developed and a comprehensive macro-micro quality evaluation method is proposed. The ACRS process can transform the material from dispersed {001}<110> low-strength plate texture to more standard {001}<100> high-strength plate texture, and obtain balanced axial and circumferential tensile strengths. Moreover, the new DAACRS process resulted in more balanced forming accuracy, inner and outer surface grain size, texture strength, and isotropic mechanical properties due to the high radial strain uniformity. Compared with the traditional completely symmetric active counter-roller spinning (CSACRS), the L̅, O̅, UD, UT{100}, UT{110}, and UT{111} are improved by 0.08265 mm, 0.00335 mm, 4.83%, 10.55%, 11.54%, and 16.34%, respectively. Further analysis provides that the allowable values of strain uniformity for the higher quality thin-walled cylinders are [Uε(PEEQ)]=0.365 and [Uε(Max Principal)]=0.438. These results increase the understanding of the strain change, microstructure evolution, and mechanical properties change mechanism of the CRS process, thereby providing important guidance for improving the CRS process and forming quality.

Identification and evaluation of the evolution stage of the agricultural machinery industry cluster in Shandong Province

AbstractAgricultural machinery industry clusters have great potential to solve key technological problems in China, and it is crucial to accurately identify the stage of cluster evolution. Based on the location entropy method, this paper finds that the location quotient coefficient is greater than 1.2 and the average annual growth rate is 1.11%, which indicates that the agricultural machinery industry in Shandong Province has a high degree of agglomeration, but the agglomeration speed is slow. Using the Groundings agglomeration—Economic network—Social network—Service system model, it is found that the agricultural machinery industry cluster in Shandong province is in the growth stage, in which the service system has the most significant influence on its development level. The weights of service system, social network, economic network, and basic resource aggregation derived from the Analytic Hierarchy Process model are 0.410, 0.321, 0.151, and 0.118, respectively, where agglomeration degree of the agricultural machinery industry, raw material production of agricultural machinery enterprises, exchange of tacit knowledge and intermediary service level are the four indicators with the greatest weights in the influences on sustainable development of the agricultural machinery industry. Because of the strong fuzzy nature between the indicators, this paper applies the Fuzzy Comprehensive Evaluation method to quantify the stage of evolution of Shandong Province's agricultural machinery industry cluster.

Exploring Sustainability in Wineries: Evaluating Food Safety and Environmental Management Aligning with the Farm to Fork Strategy

The Farm to Fork (F2F) Strategy, a key initiative of the European Commission under the European Green Deal, strives to make the European Union’s (EU) economy sustainable. Focused on the food system, the F2F Strategy prioritizes sustainability in agriculture, eco-friendly practices, biodiversity preservation, and climate change mitigation. It targets high food safety (FS) and environmental management (EM) standards across the Agri-food Supply Chain (ASC). Addressing sustainability challenges in the wine industry, this study delves into the Wine Value Chain (WVC). Emphasizing the intricate sustainability interplay within the WVC, this study concentrates on FS and EM to ensure the long-term viability of wine production. The primary goal is to create a comprehensive sustainability evaluation method for wineries, incorporating performance indicators from FS and EM components. The methodology involves assessing Food Safety Management Systems (FSMSs), evaluating Environmental Management Systems (EMSs), investigating contamination risks, and synthesizing results into a sustainability matrix. Findings highlight commendable FS practices, such as widespread Hazard Analysis and Critical Control Point (HACCP) adoption and underscore the need for increased EM focus. Notable figures include a 76.2% adoption of the HACCP system and 68.8% of wineries implementing an EMS. Performance indicators become critical for sustainability assessment, forming the cornerstone to gauge the industry’s effective sustainability management aligned with the F2F Strategy. This study stresses the holistic integration of FS and EM practices, providing insights into workforce engagement, regulatory compliance, and sustainable objectives. This research offers a tool for evaluating and advancing sustainability in the wine industry culminating in a sustainability matrix.

Mechanical behavior and track geometry evaluation of long-span cable-stayed bridges with ballastless tracks

Ballastless tracks have been widely used in China’s high-speed railways; however, they have only recently been laid on 300 m-class cable-stayed bridges. For cable-stayed bridges with a longer span, the mechanical behavior of ballastless tracks is unclear, and the track construction acceptance method is incomplete, restricting the development of cable-stayed bridges with ballastless tracks. Taking four 300–1000 m-class cable-stayed bridges as research objects, this study established static track–bridge interaction models and dynamic vehicle–bridge coupled models. By evaluating static and dynamic indices, the feasibility of laying ballastless tracks and operating high-speed trains at 350 km/h on cable-stayed bridges was analyzed. Based on the results of dynamic analysis and track geometry evaluation, a 40 m chord was proposed for track geometry acceptance on cable-stayed bridges. The accuracy of the simulation results was verified through the measured data from the Xi-Cheng Railway. The numerical results showed that the 300–1000 m-class cable-stayed bridges with ballastless tracks had good static and dynamic characteristics. The 300 m baseline was unsuitable for the long-wave irregularity evaluation of tracks on cable-stayed bridges, and the 60 m chord was easily affected by wavelengths above 200 m, leading to misjudgment of the evaluation results. The 5 mm limits of the 40 m chord could be used for track geometry acceptance on cable-stayed bridges. Finally, a comprehensive evaluation method for track geometry, namely 10 m chord, 40 m chord, and minimum vertical curve radius, was formed.

Research on an evaluation rubric for promoting user's continuous usage intention: a case study of serious games for Chinese cultural heritage.

The sustainable development of serious games dedicated to Chinese cultural heritage faces challenges due to the lack of prolonged user engagement and iterative optimization based on long-term user feedback. This situation not only hinders the sustainable growth of these games but also limits the transmission of Chinese cultural heritage, a problem that demands urgent attention yet remains under-acknowledged. This study synthesizes literature to unearth user needs from three dimensions: motivational use, quality requirements of games, and continuous usage intention. It identifies 14 influential factors, including cognitive satisfaction, immersion satisfaction, and achievement satisfaction. Drawing from the User Experience Rubric for Educational Games-CH (UEREG-CH) evaluation rubric and the Delphi method, these factors are expanded into an evaluation system model comprising six primary indicators, 14 secondary indicators, and 38 tertiary indicators. The analytic hierarchy process (AHP) is utilized for expert scoring to assign weights to each indicator. This is combined with the fuzzy comprehensive evaluation method to arrive at a final user score of Z = 3.4228, indicating that the evaluation rubric is close to 'good' and has received positive user feedback. Ultimately, this generates an evaluation rubric tailored to the specific context of serious games for cultural heritage. By integrating qualitative and quantitative methods, this paper confirms the scientific and rational nature of the evaluation rubric. The study aims to establish a user-approved rubric that encourages continuous usage intention, thereby providing effective guidance for game developers and assisting users in selecting appropriate games, while also addressing the theoretical gap in the field of evaluation for serious games related to cultural heritage.

Safety assessment of existing glass curtain wall based on fuzzy entropy and comprehensive cloud

The occurrence of safety incidents for existing glass curtain walls (EGCWs) pronounced menace to the security of both lives and property. Undertaking safety assessment for EGCWs carries essential practical significance. However, current fuzzy evaluation methods overlook the uncertainty of indicator weights and the intricacies of rank attribution. In response, this paper proposes a novel approach to the safety assessment of EGCWs. This research establishes a framework of evaluation indicators for EGCWs and divides the safety ranks of each indicator into four tiers: Safe, Mild risk, Moderate risk, and High risk. Quantitative and qualitative indicators are quantified via the variable fuzzy cloud algorithm and cloud model. The information cloud combination weighting method is introduced to determine the weight clouds of indicators. Finally, a two-dimensional assessment result is derived using an improved fuzzy comprehensive evaluation method and fuzzy entropy. The exemplified outcomes demonstrate that this approach captures the safety status of evaluation subjects based on risk ranks, and fuzzy entropy addresses two issues: inconsistent level attribution and the comparison of identical risk ranks. The appraisal method further unveils the safety details of EGCWs, with findings that align consistently with the actual situation.

Comprehensive evaluation of energy absorption characteristics of Al‐CFRP hybrid tube under radial impacts

AbstractThis paper aimed to investigate the energy absorption characteristics and damage mechanism of carbon fiber reinforced plastics/aluminum (Al‐CFRP) under radial impact. In this study, the damage mode of the hybrid tube is analyzed by falling hammer impact experiments, and the correctness of the finite element model is verified by comparing the experimental and numerical simulation results. Then, the damage mechanism of the hybrid tube under impact loading and the effects of the increase of the fiber angle, the wall thickness of Aluminum, and the number of outer CFRP layers on the impact resistance were analyzed according to the model. The comprehensive performance model of the hybrid tube was established by using the complex scale comprehensive evaluation method, and the genetic algorithm was used to optimize the hybrid tube and determine its optimal performance under radial impact load. The results show that the Al‐CFRP hybrid tube's overall stiffness and deformation resistance under radial impact is improved with the increase of the fiber angle, the wall thickness of the Al tube, and the number of outer CFRP layers. Combined with the parametric analysis of the numerical simulation results, a comprehensive performance evaluation model based on the complex proportionality assessment method (COPRAS) was developed and a genetic algorithm (GA) under back propagation (BP) neural network prediction was used. The optimal hybrid tube form with the best overall performance under radial impact was obtained using GA with BP neural network prediction.Highlights The energy absorption characteristics of hybrid tubes under radial impact are investigated A comprehensive performance evaluation model of hybrid pipe based on the complex proportional assessment method (COPRAS) is developed The failure process and energy absorption mechanism of the hybrid pipe under radial impact are analyzed A genetic algorithm (GA) with backpropagation (BP) neural network prediction was used to obtain the hybrid pipe form with the best overall performance under radial impact

Comprehensive quality evaluation of Magnolia officinalis leaves based on wavelength fusion fingerprint, content determination, and antioxidant activity analysis

Abstract A valid, novel, and comprehensive evaluation method for assessing the quality of Magnolia officinalis leaves (MOLs) from different origins has been established based on multiwavelength fusion fingerprint, quantitative analysis, and antioxidant activity screening. The four wavelength fingerprints for MOL samples at 258, 266, 290, and 327 nm were collected by high performance liquid chromatography, and then data fusion was conducted. In addition, the content of multiple components was determined by high performance liquid chromatography at four wavelengths. 1,1-Diphenyl-2-pyridyl hydrazine scavenging assay was applied to study in vitro antioxidant activity. The effective distinction of 18 batches of MOLs was realized based on hierarchical cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis combined with multiwavelength fusion fingerprint. The orthogonal partial least squares discriminant analysis model exhibited huge advantages in distinguishing among different samples and screening three quality markers of the tested samples, including rutin, isoquercitrin, and chlorogenic acid. This established method of multitechnology fusion is simple, reliable, and efficient for the qualitative and quantitative bioactivity evaluation of MOLs. This study aims to investigate the development of new medicinal parts of traditional Chinese medicines (TCMs), so as to enhance the efficiency of utilizing TCM resources and promote the high-quality development of the TCM industry.

Battery inconsistency evaluation based on hierarchical weight fusion and fuzzy comprehensive evaluation method

Inconsistency is a crucial factor that affects the lithium-ion battery pack performance. Reliable cell inconsistency evaluation is essential for the efficient and safe usage of batteries. This study develops a fuzzy comprehensive evaluation (FCE) method based on hierarchical weight fusion to quantitatively evaluate the cell inconsistency. First, through an analysis of how the internal parameters change as the battery ages, the capacity, ohmic resistance, open circuit voltage and the constant current charging time are extracted as the inconsistency indicators from the collected data. They not only reflect the static and dynamic properties of batteries, but also cover the static, charging, and discharging processes. Next, a novel hierarchical weight fusion approach is proposed to achieve weight assignment by combining the entropy weight method, criteria importance through inter-criteria correlation (CRITIC) method and sequential relationship analysis (G1) method, which can incorporate the benefits of the objective and subjective weighting methods. Finally, the FCE method is utilized to quantitatively evaluate the cell inconsistency of lithium-ion batteries. Experimental results demonstrate that the proposed hierarchical weight fusion-based FCE approach can provide a clear evaluation of the degree of inconsistency across various datasets. Compared with the entropy weight-based, CRITIC-based and G1-based methods, the proposed method is more rational and comprehensive.

The Evolution and Economic and Social Effects of the Spatial and Temporal Pattern of Transport Superiority Degree in Southern Xinjiang, China

Transportation significantly influences economically underdeveloped arid regions, impacting economic growth and social progress. Analyzing Transport Superiority Degree (TSD) and its implications in such regions is crucial. A new arid region-specific evaluation framework addresses traditional limitations by considering indicators like route connectivity and desert interference. This article conducts an empirical study using Southern Xinjiang as a research case. It combines comprehensive evaluation methods, spatial autocorrelation methods, spatial Durbin models, and coupling coordination models to depict Transport Support Capability (TSC), Transport Access Capacity (TAC), and Transport Guarantee Capacity (TGC) at different scales in Southern Xinjiang from 2000 to 2020. The study reveals spatial patterns, evolutionary characteristics, economic impacts, and social effects of TSD at various scales. Key findings include: (1) Rapid expansion of transportation infrastructure in Southern Xinjiang. The levels of TSD at different scales have gradually increased, and spatial and temporal pattern differences are evident. At the county level, TSD forms a “core-periphery” spatial pattern centered around the Southern Xinjiang Railway, with “high-high” agglomeration areas centered around Kashgar city and “low-low” agglomeration areas centered around Qiemo County. (2) Prefectural-level TSD improvements have limited impacts on regional development, while county-level TSC, TAC, TGC, and TSD positively affect economic and social growth but also exhibit competitive effects. (3) TSD is transitioning from non-coordinated to coordinated development with economic and social progress at different scales. This research informs transportation facility evaluation in arid regions.

Comprehensive evaluation of green mine construction level considering fuzzy factors using intuitionistic fuzzy TOPSIS with kernel distance.

With increasing concerns about climate change and resource-environmental limitations, the green development of the mining industry has become mainstream and gained much support. Driven by the concept of sustainable and green development, China has made the advancement of green mine construction a crucial part of establishing an eco-society and has put forward the overall goal of green mines. An important future strategy is to evaluate a large number of mines. However, developing scientific, reliable, and comprehensive index systems and evaluation methods is extremely difficult because of the objective complexity of green mine evaluation and the fuzziness of some indicators. The kernel method and intuitionistic fuzzy set can effectively handle these problems. This study proposed a comprehensive evaluation index system and a hybrid evaluation method based on the kernel distance measure and intuitionistic fuzzy TOPSIS method. The index system contains 22 indicators considering six aspects: mining area environment, resource development mode, comprehensive utilization of resources, energy saving and emission reduction, technical innovation, and corporation management. The hybrid evaluation method was applied to the practical assessment of ten green mines in Panxi, China. Comparative analyses were carried out to demonstrate its applicability and sensitivity. The results verify that the hybrid method can fully depict the construction achievements of green mines in all aspects with strong reliability and stability. This approach is a valuable reference for evaluators and decision-makers in government departments.

Evaluation Model on Activation Classification of Coal Mine Goaf Ground Considering High-Speed Railway Loads

The construction and expansion of high-speed railway networks in China has been occurring at a fast pace, resulting in some lines crossing through coal mine goaf sites. However, the embankment and train loads may trigger the activation of the coal mine goaf ground, posing a threat to traffic safety. To ensure the safety of construction and railway lines, an evaluation model on the activation classification of coal mine goaf ground, taking into account the high-speed railway load, is proposed, which is mainly applicable for middle–deep and level goaf areas using a longwall mining method. Firstly, 12 influencing factors are selected as the underlying evaluation indexes, and the catastrophe progression method model for evaluating the coal mine goaf ground stability is constructed. The findings of the evaluation were found to align with the actual results, indicating the reliability of the model. Then, the additional stress calculation model for high-speed railway ground with different embankment heights, train speeds, and axle loads was established, and the train load disturbance depth with a 5% criterion was determined. The influence degree of load on high-speed railway was divided, and the weight of each factor was determined. Finally, the extension comprehensive evaluation method was used to unite the stability grade of the coal mine goaf site and the influence degree of the train, so the evaluation model on activation classification was proposed. The accurateness and reliability of the proposed model was verified using the Taijiao high-speed railway cases and the model test.

Measurement and Evaluation Method of Distributed Optical Fiber Acoustic Sensing Performance

Distributed acoustic sensing incorporates multiple indicators, and there exists a mutually constraining relationship among these indicators. Different application fields have varying requirements for indicators. Therefore, indicator testing and comprehensive evaluations are crucial for engineering applications. In this paper, we conducted a theoretical analysis of key indicators, including frequency response, sensitivity, spatial resolution, sensing distance, multi-point perturbation, and temperature influence. The indicator test scheme was developed, and a test system was constructed. The test data were analyzed and compared in the time-frequency domain. A performance evaluation method for distributed acoustic sensing, based on the analytic hierarchy process, is proposed, and a comprehensive evaluation example focused on high-frequency applications is presented. The results show that the test scheme and method presented in this paper can accurately measure the upper limits of each indicator of distributed acoustic sensing. The proposed comprehensive evaluation method enables the assessment of sensor performance and applicability based on engineering practices. It addresses the challenge of evaluating distributed acoustic sensing with multiple indicators and offers an efficient approach for equipment development and engineering applications.

Optimization of water quality evaluation index using information sensitivity method and variable fuzzy model for the Guo River, China.

The more water quality evaluation indicators, the greater the amount of water quality evaluation calculation. Under the requirements of evaluation accuracy, the index screening method is usually used to optimize water quality evaluation index to reduce the calculation amount of water quality evaluation. Taking Mengcheng Gate of Guo River as an example, the information sensitivity index screening method was used to simplify the water quality evaluation index system from 17 to 12 indicators. The variable fuzzy comprehensive evaluation method was used to compare and evaluate the original index system and the optimal index system. The results showed that the water quality results of the optimal index system are consistent with the original index evaluation results. And the water quality of Mengcheng Gate is basically stable at class I level. The information sensitivity method reduced the number of indicators by 29.41%. The error between the water quality evaluation results based on the optimal indicators and the original indicators is less than 10%. The maximum error, minimum error, and average error are 8.92%, 0.08%, and 2.46%, respectively. It revealed that the information sensitivity method can eliminate the information redundancy while retaining the information of the original index system. It can also reduce the calculation amount of water quality evaluation in the future. The variable fuzzy comprehensive evaluation method can reasonably reflect the complex nonlinear relationship between water quality index and water quality category. This accuracy has practical significance for guiding the optimization of water quality evaluation index system, improving the efficiency of water quality evaluation. This model provides a scientific basis for indicator selection methods in similar river water quality evaluations.

A comprehensive approach to evaluate coastal dune evolution in Haiyang, China

Coastal dunes record the evolutionary process of coastal dynamic geomorphological systems, and provide valuable information on climate change, sea level changes, environmental evolution. These dunes are essential for global change research. In view of the dynamic changes in coastal dunes caused by extreme weather, coastal erosion and human activities, we propose a comprehensive evaluation method for coastal dune evolution, which monitors Haiyang Ten Thousand Meters Beach of China from three perspectives: point, line, and surface. This method integrates LiDAR, GNSS, and RS technologies. The research results indicate that between 2016 and 2018, 68% of the GNSS point measurements in 22 survey profiles of coastal dunes were eroded along the foreshore. During 2011-2020, the coastline based on the RS data basically remained stable; only the estuarine district underwent significant changes, and the overall average change rate was 1.32 m/a. The overall morphological evolution of coastal dunes obtained by LiDAR in 2018 was relatively stable, but there was a weak erosion trend in the foreshores of the coastal dunes. This study is beneficial for providing precise targets for remediating and restoring eroded coastal areas in the future. Furthermore, it can provide technical support and informational information for ecological environment protection, coastal erosion prevention and environmental evolution in the Haiyang Ten Thousand Meters Beach Marine Nature Reserve.

An Analytic Hierarchy Process Method to Evaluate Environmental Impacts of In Situ Oil Shale Mining

The great demand for oil shale resource development and the corresponding threats to the environment have resulted in the urgent need to assess the impact of oil shale in situ mining on the environment. In this paper, based on an analysis method developed by the previous literature and the Delphi technique, three secondary indicators and ten tertiary indicators were selected. The weights of the indicators at all levels were subsequently calculated. The results identify environmental capacity, groundwater risk and prevention, and cleaner production as having the largest weights in the indicator system. Following this, the typical three-level indicators with the largest weight and content related to carbon emissions were introduced in detail, and combined with the calculated weight of each indicator, the comprehensive evaluation index method was used to determine the comprehensive evaluation model for the environmental impact of oil shale in situ mining. The comprehensive evaluation model value, PA, of the target layer (the primary indicator) under two different heating methods, combustion heating and electric heating, were then calculated based on the oil shale in situ mining area in Fuyu City, Jilin Province, China. This study introduces carbon-emission-related elements into the three-level indicator evaluation calculation model, which is a more accurate and advanced comprehensive evaluation method.

Research on optimization method of railway construction scheme based on multidimensional combination weighting and improved grey theory

The optimization of railway construction schemes is a complexity system engineering task with multiple dimensions, diverse conditional constraints, and multifaceted objective assessments. The decision-making and scheme evaluation entail subjectivity, randomness, and fuzziness. To address the comprehensive optimization challenge in construction schemes effectively and efficiently, we investigate an optimization method for railway construction schemes. This method is based on multi-dimensional combination weighting and improved grey theory. After analyzing the primary influencing factors, we established a railway construction plan optimization index system comprising 4 dimensions and 18 factors. The weight combination coefficient is determined using the pros and cons solution distance method, and the optimal weight set for the index is determined through the multi-dimensional combination weighting approach. Utilizing the method of superior and inferior solution distance coupled with grey theory, we ascertain the order of advantages and disadvantages for each construction scheme, subsequently achieving construction scheme optimization. To illustrate this, we employ the optimization process for a high-speed railway section in Guangxi as an exemplar. The verification results indicate that the gray relative closeness values for schemes A, B, and C are 0.7089, 0.4813, and 0.4463, respectively. Scheme A has the highest gray relative closeness value, thus making it the optimal route scheme. The optimal results obtained through this method align with the outcomes of expert validation and existing research, thereby validating the effectiveness and practicality of the model. By employing a multidimensional combination weighting method, the deficiencies of traditional indicator weight calculations are mitigated, resulting in indicator weights that are more reflective of the actual circumstances. At the same time, the application of improvements in the grey theory comprehensive evaluation method enables the integration and computation of indicator data for each construction plan. Through the intuitive representation of grey relative closeness, the advantages and disadvantages of each plan are effectively characterized. This enhances the scientific rigor and applicability of the railway construction plan optimization process. The research findings can serve as a reference for similar railway construction scheme selection problems in the future.

Using Particle Swarm Optimization with Backpropagation Neural Networks and Analytic Hierarchy Process to Optimize the Power Generation Performance of Enhanced Geothermal System (EGS)

The optimization of the production scheme for enhanced geothermal systems (EGS) in geothermal fields is crucial for enhancing heat production efficiency and prolonging the lifespan of thermal reservoirs. In this study, the 4100–4300 m granite diorite stratum in the Zhacang geothermal field was taken as the target stratum to establish a numerical model of water-heat coupling of three vertical wells. However, relying solely on numerical simulation for optimization is time-consuming and challenging for the determination of the globally optimal production plan. The present study proposes a comprehensive evaluation method for optimizing the performance of EGS power generation based on the integration of particle swarm optimization with backpropagation neural network (PSO-BPNN) and analytic hierarchy process (AHP). Five different PSO-BPNN models were constructed based on the numerical simulation data to predict different EGS power generation performance indexes, including the production temperature, the injection pressure, the total electricity generation, the electric energy efficiency and the levelized cost of electricity. Based on these PSO-BPNN models, the weights of various thermal development evaluation indexes were calculated by AHP to conduct a comprehensive evaluation of the power generation performance of the three vertical wells EGS. The results show that the PSO-BPNN model has good prediction accuracy for EGS prediction of various performance indicators, with a coefficient of determination (R2) exceeding 0.999. The AHP evaluation of all production schemes reveals that the optimal power generation scheme entails a well spacing of 580 m, water injection rate of 56 kg/s, injection temperature of 38 °C and fracture permeability of 2.0 × 10−10 m2. Over a span of 30 years, this scheme can provide a total power generation capacity amounting to 1775 GWh, with an associated LCOE value of 0.03837 USD/kWh. This not only provides a reference for the development and optimization of geothermal systems in the Zhacang geothermal field but also provides a new idea for the optimization design of other geothermal projects.