Combined Evaluation Model Research Articles

A new performance evaluation indicator for the LEE Jong-wook Fellowship Program of Korea Foundation for International Healthcare to better assess its long-term educational impacts: a Delphi study.

The Dr. LEE Jong-wook Fellowship Program, established by the Korea Foundation for International Healthcare (KOFIH), aims to strengthen healthcare capacity in partner countries. The aim of the study was to develop new performance evaluation indicators for the program to better assess long-term educational impact across various courses and professional roles. A 3-stage process was employed. First, a literature review of established evaluation models (Kirkpatrick's 4 levels, CIPP model, OECD DAC criteria) was conducted to devise evaluation criteria. Second, these criteria were validated via a 2-round Delphi survey with 18 experts in training projects from May 2021 to June 2021. Third, the relative importance of the evaluation criteria was determined using the analytic hierarchy process (AHP), calculating weights and ensuring consistency through the consistency index (CI) and consistency ratio (CR), with CR values below 0.1 indicating acceptable consistency. The literature review led to a combined evaluation model, resulting in 4 evaluation areas, 20 items, and 92 indicators. The Delphi surveys confirmed the validity of these indicators, with content validity ratio values exceeding 0.444. The AHP analysis assigned weights to each indicator, and CR values below 0.1 indicated consistency. The final set of evaluation indicators was confirmed through a workshop with KFIH and adopted as the new evaluation tool. The developed evaluation framework provides a comprehensive tool for assessing the long-term outcomes of the Dr. LEE Jong-wook Fellowship Program. It enhances evaluation capabilities and supports improvements in the training program's effectiveness and international healthcare collaboration.

Adaptability Evaluation of Power Grid Planning Scheme for Novel Power System Considering Multiple Decision Psychology

With a substantial fraction of renewable energy integrated into the electrical grid, the new power system urgently requires grid planning scheme displaying adaptability to different energy types and their volatility. Considering the indeterminacy of renewable energy generation output and the different attitudes of decision-makers towards its risk, this paper proposes an adaptability assessment methodology for power grid planning schemes considering multiple decision psychology. First, an evaluation indicator framework is established based on the adaptive requirements of the grid planning for novel power system, and the weights of indicators are calculated based on an improved AHP-CRITIC combination weighting method. Second, improved cumulative prospect theory (ICPT) is adopted to improve to the calculation method of the distance between the evaluation program and the positive and negative ideal programs in the GRA and TOPSIS, which effectively characterize the different decision-making psychologies, and a combination evaluation model is constructed based on a cooperative game (CG), namely, an adaptability evaluation model of grid planning schemes for novel power systems based on GRA-TOPSIS integrating CG and ICPT. Finally, the proposed model serves to evaluate grid planning schemes of three regions in China’s 14th Five-Year Plan. The evaluation results show that the adaptability of the schemes varies under different decision-making psychologies, and under the risk-aggressive and loss-sensitive decision-making psychologies, grid planning scheme of Region 1 with the greatest accommodation capacity of renewable energy is preferable.

Multi scale evaluation and analysis of international trade objectives of port cities

The analysis of the multi-scale evaluation of port city’s international trade goal is conducive to the sustainable development of port city’s international trade. In order to make a more in-depth study on the realization ability of port city’s international trade sustainable development goal, this paper proposes a new multi-scale evaluation method of port city’s international trade goal. This method selects the evaluation indexes, uses the improved normalization method to process the indexes, uses the combination of AHP and factor analysis method to form the subjective and objective combination weighting method, brings the processed indexes into the least square optimization combination evaluation model, calculates the index weight, and uses the fuzzy evaluation method to carry out multi-scale index evaluation on the international trade of port cities to realize its multi-scale evaluation and analysis. The results show that the standardized index of Shanghai’s foreign trade dependence is 0.0056, indicating its independence in international trade. In the comprehensive evaluation, the evaluation values of Shanghai, Tianjin, and Guangzhou are 92.56, 87.89, and 88.45, respectively, which are very close to the actual results, which shows that the accuracy of the evaluation method is high, and provides a theoretical basis for the sustainable development of international trade in port cities.

Evaluation Analysis on Influences of AHP-TOPSIS-Model-Based Artificial Intelligence on College Students Learning

In recent years, the field of artificial intelligence has witnessed rapid development and continuous technological advancements. It has found widespread application in various domains, exerting profound influences on all aspects of human social life. This article focuses on evaluating the impact of artificial intelligence on college students' learning. Based on a survey of 4605 participants, the collected data was transformed into numerical values and underwent preliminary data processing. An indicator evaluation system was established, encompassing priority, scientificity, and feasibility, in order to construct a comprehensive evaluation framework. By conducting both objective and subjective analyses of the survey questions, the obtained weight values were subjected to consistency tests, which confirmed their reliability. Through the application of the Analytic Hierarchy Process (AHP), the final weights were determined, and the top eight indicators were selected for evaluation. An AHP-TOPSIS combined evaluation model was developed, which concludes that artificial intelligence has significantly influenced college students' learning and yielded positive effects. The novelty of this article lies in the utilization of the AHP-TOPSIS combined evaluation model, which incorporates the advantages of both models and avoids the limitations associated with a single model, such as biased perspectives and low reliability.

Evaluating effect of micro-spray on tomatoes for resisting summer heat stress using a Fuzzy Borda combination evaluation model

Micro-spray is commonly used to improve the growing environment of plants to avoid growth inhibition due to high temperatures in greenhouses in summer. In this study, the effects of micro-spray on growth and physiological characteristics of tomato plants grown in a Venlo-type greenhouse were observed using a combined micro-spray and drip irrigation (MSDI) system for two growing. Therefore, four single integrated evaluation methods, TOPSIS, PCA, RSR, and VIKOR were used to evaluate the different indicators in an integrated manner to avoid the limitation of a single indicator under two irrigation methods. The results of the study showed that the values of effective quantum yield of PSII (ФPSII) for tomatoes cultivated under MSDI treatment were higher than those obtained under DI treatment. However, when the air temperature was below 35 °C and photosynthetically active radiation (PAR) was below 820 μ mol/m2/s, the increase in ФPSII value was ranged from 13% to 23% under MSDI. Once the air temperature exceeded 35 ℃, then a short time (1 min) micro-spray was less effective in relieving heat stress; and the increase of ФPSII ranged from 6% to 13%. Meanwhile, it was found that the TOPSIS, PCA, and RSR were suitable for studying the rapid quality evaluation of the tomato cultivated under MSDI because their ranking results had a high Spearman correlation coefficient of 0.965 with the Fuzzy Borda combination evaluation (FB) model. Comprehensively evaluating the quality of tomatoes cultivated under different irrigation methods, the results of the FB model proved that the MSDI was better than the DI because the comprehensive score of the MSDI was higher than the DI. MSDI took up five spots in the top six scores in the two years of the FB model.

Optimization algorithms for light pollution management based on TOPSIS-non-linear regularization model

Rapid urbanization and economic development have inevitably led to light pollution. However, currently the world has not yet formed a unified technical standard for light pollution, and light pollution cannot be effectively controlled when the environmental protection department is unable to operate. To effectively solve this problem, this paper establishes a combined weight ideal point method evaluation model based on TOPSIS evaluation method to obtain comprehensive index weights to evaluate the light pollution risk levels of four different land types in urban, suburban, rural and nature reserve areas in Beijing, China, and uses one-way ANOVA to test the differences among the four regions. Based on the Random Forest algorithm to determine the three variables with the top three feature importance weights, and based on the nonlinear optimization algorithm, using the SLSQP method, the optimal parameter combinations with the smallest cost are obtained after iteration, so as to put forward three feasible intervention strategies such as adjusting the design of the nightscape lighting, reducing the time of nonessential lighting, and rationally planning the layout of the city’s lighting, etc., to solve the light pollution problem, which effectively promote the urban nightscape lighting’s it effectively promotes the healthy and sustainable development of urban nightscape lighting.

Research on Light Pollution System Based on Innovative Evaluation Method and Particle Swarm Optimization Grey Prediction Method

The control of light pollution is an important part of people's urban health. An accurate index system of quantitative light pollution level is of great significance for controlling light pollution, saving energy, and improving social happiness index. After obtaining the combined weight evaluation model, in order to verify the reliability of the index system in various regions, based on the grey prediction theory, combined with the advantages of PSO algorithm in model accuracy and predictability, the light pollution risk level in Shanghai was evaluated and predicted, and specific intervention strategies for light pollution remediation were proposed.

A systematic framework to improve the digital green innovation performance of photovoltaic materials for building energy system

Under the current ‘double carbon’ policy, the building materials manufacturing industry has seriously restricted the improvement of social and environmental benefits. Digital green innovation (DGI) in photovoltaic building materials enterprises (PBMES) plays a crucial role in solving the problems of high-quality environmental and economic development. In order to make the DGI of PBMES more effective, it is very critical to evaluate the performance of the DGI activities of PBMES. First, the evaluation index system is constructed. Then, it constructs the theoretical framework of the DGI performance evaluation of PBMES. After that, on the basis of combining various evaluation methods, a combination evaluation model based on compatibility and consistency was constructed and the convergence test and consistency test of the combination evaluation results were carried out by means of the variance method and Spearman rank correlation coefficient, which verified the scientificity and validity of the method. Finally, using the evaluation model, 16 PBMES were empirically studied. It reflected that the DGI performance evaluation index system of PBMES is composed of four indexes, namely, technology input, economic output, scientific and technological output, and social effect. The key factors affecting the DGI performance of PBMES are the investment in talent training, the proportion of digital technology in green products, the success rate of digital innovation product development increased by DGI cooperation, and the digital level of adopting environmental management system. This article combines consistency-based evaluation methods to not only obtain reasonable evaluation results, but also fully utilize multi-level methods to better describe the evaluation object. The means provided in this article are a new way to solve the DGI performance evaluation of PBMES.

Evaluation of Online Learners’ Learning Performance Based on Fuzzy Borda Method

Since the traditional evaluation system of learning focuses only on the summative evaluation of learners’ test scores, ignoring the process evaluation of learners in learning process, the evaluation system should not only consider the content of the online learning process but also that of face-to-face classroom teaching process to evaluate learners’ learning performance in multiple dimensions and levels. This approach evaluates online learning more reasonably, operably and feasibly. To overcome limitation of using more than one method in the evaluation of learning performance, the learning performance of online learners was first evaluated using the principal component analysis method, entropy method, comprehensive indicator method, and TOPSIS method. Based on these four evaluation results, a combination evaluation model of online learners’ learning performance was constructed. The Fuzzy Borda method was used to evaluate nine administrative classes of accounting majors in three colleges and universities in Hainan. The results show that simply using a single evaluation method to evaluate the learning performance of online learners has defects, and the evaluation results are too biased. By using the Fuzzy Borda method, multiple evaluation methods can be combined, allowing a single evaluation method to realize complementary advantages and obtain more comprehensive and credible evaluation results. Using the Fuzzy Borda method to systematically evaluate the learning performance of online learners improves the scientificity of evaluation results and provides a new idea and method for the evaluation of online learning performance. The results of this study have significant reference value for using scientific evaluation methods and objective data to evaluate online learning performance, rank online learners scientifically, and summarize teaching experience to improve online learning performance.

Water and nitrogen management scheme of melon based on yield−quality−efficiency matching perspective under CO2 enrichment

Rising CO2 concentration in the atmosphere may modulate the response of plants to water and nitrogen, and the existing research is not sufficient to support the fine management of water and nitrogen under CO2 rise. To determine the optimal water and nitrogen strategy for melon production under CO2 enrichment in the future, we conducted an experiment with 12 treatments over three growing seasons. The effects of water nitrogen coupling on the yield, quality, and water−nitrogen use efficiency of oriental melon (Cucumis melo L. Qianyu No. 6) under CO2 enrichment were investigated and evaluated comprehensively. The treatments included two CO2 concentrations, C1 (400 ppm) and C2 (800 ppm), three irrigation levels, I1 (80% evaporation (Ep)), I2 (100% Ep), and I3 (120% Ep); two nitrogen levels, N1 (S: 184.77 kg ha–1, F: 147.21 kg ha–1) and N2 (S: 369.54 kg ha–1, F: 294.42 kg ha–1). The result showed that the yield increased with increasing levels of irrigation and nitrogen, and enriched CO2 significantly increased the yield by 10.3 − 22.9%. N2 showed a significant promoting effect on the ratio of marketable fruit in the two spring seasons. Enriched CO2 significantly increased free amino acid of I1. C2 coupled with I1 significantly reduced nitrate content by 30.9%, 14.9% in 2020 F and 2021 S, respectively. The interaction of C*I was significant in irrigation water−use efficiency (IWUE) and nitrogen−use efficiency (NUE). In particular, C2 coupled with I2 increased IWUE by 40.5%, 18.7% and NUE by 43.9%, 13.9% in the two spring seasons, respectively. Ten indicators from three categories of yield, quality, and efficiency were used to establish the evaluation system of melon and were comprehensively evaluated based on Fuzzy−Borda model combined three single models. Based on the combined evaluation model, intermediate irrigation combined with higher nitrogen input was best for melon production under CO2 enrichment. This finding suggested that melon sustainable production should control irrigation and adequately increase nitrogen fertilizer to trade−off fruit, quality, and efficiency for the expected future higher CO2 concentrations.

Enhanced Evaluation Model Based on Classification Selection Applied to Value Evaluation of Waste Household Appliances

In the process of recycling, dismantling, and reusing household appliances, implementing extended producer responsibility (EPR) has become increasingly important. Designing a reasonable pricing mechanism for waste household appliance recycling is critical for the implementation of EPR. To address the problem of labor-intensive and experience-dependent traditional manual methods for assessing the value of waste household appliances, in this paper, we propose an evaluation method based on the subtractive clustering method and an adaptive neuro fuzzy inference system (SCM–ANFIS), which outperforms traditional neural networks such as LSTM, BP neural network, random forest and Takagi–Sugeno fuzzy neural network (T–S FNN). Moreover, in this paper, we combine the five aforementioned algorithms to design a combination evaluation model based on maximum ratio combination (CEM–MRC), which can achieve a performance improvement of 0.1% in terms of mean absolute percentage error (MAPE) compared to the suboptimal BP neural network. Furthermore, an enhanced evaluation model based on classification selection (EEM–CS) is designed to automatically select the evaluation results between the optimal SCM–ANFIS and the suboptimal CEM–MRC, resulting in a 0.73% reduction in MAPE compared to the optimal SCM–ANFIS and a 1.42% reduction compared to the suboptimal CEM–MRC. In this paper, we also validate the performance of the proposed algorithms using a dataset of waste television recycling, which demonstrates the high accuracy of the proposed value assessment mechanisms achieved without human intervention and a significant improvement in evaluation accuracy as compared to conventional neural-network-based algorithms.

Implementation of Efficiency Tracking and Evaluation Algorithm for Agricultural Product Circulation Based on Radio Frequency Data Tags and Android Platform

The article believes that the circulation efficiency of agricultural products, especially the efficiency of the circulation system of agricultural products, is the ratio of circulation output to circulation cost in the process of circulation of agricultural products. The circulation efficiency of agricultural products cannot be measured by a single indicator. The article argues that the PCA-DEA combination evaluation model can be constructed by using the market integration degree, market concentration degree, technical efficiency, consumer satisfaction, circulation spread, transaction costs, and using the principal component weight constraint cone to objectively assign DEA values. At the same time, it is necessary to develop a circulation mode of agricultural products led by leading enterprises, promote the intensive processing of agricultural products, and improve the circulation efficiency.

Evaluation of China's regional innovation capability based on simulated annealing projection pursuit model and nested fuzzy evaluation model

AbstractRegional innovation capability is an important indicator of both regional innovative and long‐term development. The purpose of this study is to build an evaluation index system for regional innovation capability in order to identify regional differences and support innovation more effectively. After establishing a reasonable evaluation value for regional innovation capability, a combination of simulated annealing optimized projection pursuit (SA–PP) and N‐layer nested fuzzy comprehensive evaluation models is used to assess China's regional innovation capabilities. The results show that the SA–PP model effectively mitigates the risk of erroneous evaluation results caused by index weight uncertainty, resulting in a more reasonable, robust, and intelligent assessment of regional innovation capability. Furthermore, the nested fuzzy comprehensive evaluation model is capable of easily resolving the evaluation factor set's heterogeneity and multilayer problems. The most significant influences on China's regional innovation capability are knowledge acquisition and enterprise innovation. The comprehensive score of the proposed combinational evaluation model manifests that provinces with strong regional innovation capabilities are mainly concentrated in the southeast coastal regions. The research results allow for precise weight determination and object ranking.

Multi-objective optimization of water and nitrogen regimes for drip-fertigated sugar beet in a desert climate

The scarcity of water resources and low water-nitrogen use efficiency largely restrict the sustainable development of sugar beet ( Beta vulgaris L.) in desert climates. A three-year field experiment was conducted to investigate the responses of taproot yield, sucrose content, sugar yield, irrigation water use efficiency, nitrogen partial factor productivity, soil nitrate nitrogen residue and economic benefit of drip-fertigated sugar beet under plastic mulch to varying water and nitrogen supplies. There were three irrigation levels (W 0.6 : 0.60 ET c , W 0.8 : 0.80 ET c and W 1.0 : 1.00 ET c in 2019 and 2020; and W 0.4 : 0.40 ET c , W 0.6 : 0.60 ET c and W 0.8 : 0.80 ET c in 2021, where ET c is the crop evapotranspiration) and six nitrogen (N) application rates (N 25 : 25 kg N ha −1 , N 60 : 60 kg N ha −1 , N 120 : 120 kg N ha −1 , N 240 : 240 kg N ha −1 , N 360 : 360 kg N ha −1 and N 480 : 480 kg N ha −1 ). The combined evaluation model based on the overall difference was further used to explore the optimal combination of irrigation amount and N rate for multi-objective optimization. The results showed that there was no significant difference in sucrose content among the irrigation treatments in the same year. Taproot yield, sugar yield, irrigation water use efficiency of both taproot yield and sugar yield increased and then generally stabilized with the increasing N rate under the same irrigation amount. Nitrogen partial factor productivity of both taproot yield and sugar yield decreased with the increase of N rate. There was no significant difference in soil nitrate nitrogen residue among the irrigation treatments under N 25 , N 60 and N 120 , but increasing N rate increased the soil nitrate nitrogen residue. Net return first increased and then decreased as N rate increased under the same irrigation amount. Based on the combined evaluation model, the multi-target optimization was obtained under W 0.6 N 120 . The results indicated that the combination of irrigation amount of 0.60 ET c and N rate of 120 kg N ha −1 was benifical for the sustainable production of drip-fertigated sugar beet in desert climates. • The combined evaluation model was used to for multi-objective optimization of water and nitrogen regimes. • Maximum sugar yield and net return were obtained under 80 % crop evapotranspiration and 120 kg N ha −1 . • Taproot/sugar yield and irrigation water use efficiency increased and then stabilized with increasing nitrogen rate. • Multi-target optimization was obtained under 60 % crop evapotranspiration and 120 kg N ha −1 for drip-fertigated sugar beet.

Structure construction, evolution analysis and sustainability evaluation of Water-Ecological-Economic system

Under the influence of human activities, the unary water cycle has been transformed into a “natural–social” dualistic water cycle, and the analysis of driving mechanism of the water system under the dualistic water cycle has become an important proposition for sustainable human-water development. This study explored the connotation, framework, and structure of the Water-Ecological-Economic (WEE) system. The WEE system encompasses water resources, society and economy, water use efficiency, water environment, and water ecology subsystems which interact functionally. And system dynamics is used to drive the evolution of system coupling. For each subsystem's characteristics, its sustainability evaluation index is proposed. MDM-TOPSIS combination evaluation model is applied to calculate the weights of indices and the sustainability comprehensive indicator of WEE system. Taking Nanyang in China as a case study, the results show that the sustainability of the WEE system has a downward trend in the early stage, but in the middle and late stages, ecological and environmental protection is considered, the sustainability level shows an upward trend with the support of several safeguard policies. The WEE system and its sustainability assessment theory proposed in this study will provide scientific support to water resources management and sustainable development planning.

Performance Evaluation of Enterprise Collaboration Based on an Improved Elman Neural Network and AHP-EW

In order to mitigate the influence of human subjectivity on indicator weights in the performance evaluation of enterprise collaboration, and explore the nonlinear relationship between the enterprise collaboration influencing factors and the evaluation results, this paper propose a combined performance evaluation model based on AHP-EW and an improved Elman neural network. Firstly, based on the characteristics of collaboration among manufacturing enterprises, the evaluation system for the collaborative performance of manufacturing enterprises is constructed from three dimensions. Moreover, this study combines subjective and objective weighting methods to obtain comprehensive weights that take into account both expert experience and objective information. Then, an improved Elman neural network is proposed and trained to predict and evaluate the collaborative performance indicator data, which greatly shortens the evaluation time and improves evaluation accuracy. The experimental results show that the proposed model has a faster convergence speed and higher accuracy, which will provide a valuable reference for decision making and the management of enterprise collaboration.

Tomato Comprehensive Quality Evaluation and Irrigation Mode Optimization with Biogas Slurry Based on the Combined Evaluation Model

Scientific and reasonable water and fertilizer regimes positively affected crop growth, yield, fruits quality and soil environment improvement. As a liquid quick-acting organic fertilizer to substitute chemical fertilizers, biogas slurry has been widely used in agricultural production. However, the lack of research on the proper comprehensive quality evaluation model and irrigation mode under biogas slurry limits the promotion and large-scale application of biogas slurry in agricultural production. In this study, three biogas slurry (BS) ratio (1:4BS, 1:6BS, 1:8BS; volume ratio of biogas slurry to water), three irrigation levels (W1, W2, W3) and three fertilizer control treatments (CF1, CF2, CF3) were conducted in field experiments. Eleven single indexes from four type qualities (external quality, taste quality, nutrition quality, storage and transportation quality) were adopted to establish the comprehensive evaluation index system of tomato. The principal component analysis, grey correlation analysis, membership function analysis and TOPSIS analysis model (based on the combination of objective entropy method and subjective analytic hierarchy process) were used to estimate the comprehensive quality of tomato fruits. Moreover, the objective combination evaluation mode based on overall diversity was used to evaluate the results obtained from the four independent comprehensive evaluation methods. The aim is to mitigate inconsistencies of multi-attribute evaluation models. The results showed that biogas slurry application was beneficial to the accumulation of aboveground biomass under the same irrigation amount, which can effectively improve the sugar to acid ratio and lycopene content of tomato. T3 (1:4BS, W3) and T1 (1:4BS, W1) obtained the highest yield and water use efficiency (WUE), respectively. The results of Kendall consistency test and Pearson correlation coefficients showed that there were good compatibility and high consistency among the four independent comprehensive evaluation models, and the combined quality evaluation model can be performed directly. As the correlation coefficients between combined evaluation model and each of four independent methods reached 0.965, the combined evaluation model was capable of reducing the differences of four independent comprehensive evaluation model. The combined quality evaluation results showed that T2 (1:4BS, W2) recommended strongly in this study could effectively improve the yield, quality and WUE of tomato.

Study on site selection combination evaluation of pumped-storage power station based on cycle elimination — Based on the empirical analysis of North China

Energy structure reform is the common choice of all countries to deal with climate change and environmental problems. Pumped-storage power station (PPS) will play an important role in the green and low-carbon energy era of “source-grid-load-storage” synergy and multi-energy complementary optimization. In this context, this paper puts forward a PPS selection evaluation index system and combination evaluation model for energy internet. First of all, on the basis of the construction conditions of traditional PPS, considering the multi-energy complementary demand of energy internet, a three-dimensional evaluation index system of “hydrology & geological conditions”, “construction conditions” and “energy structure demand” has been established. Secondly, concepts such as degree of center cohesion, similarity threshold and core method set are introduced to construct a cycle elimination mechanism and eliminate the edge single evaluation method (SEM) to improve the scientificity of combination evaluation. Site selection combination evaluation of PPS based on cycle elimination is constructed, and effectiveness measure test of site selection combination evaluation method is defined. Finally, PPS in North China is taken as an example to verify the effectiveness of the model and the sensitivity analysis is carried out. The research shows that the effectiveness of the combination evaluation method is not only determined by the mechanism of the method itself, but also affected by the consistency of the SEM set, and the cycle elimination mechanism can improve the effectiveness of the combination evaluation method. The evaluation index system, site selection model based on cycle elimination and effectiveness measure are constructed in this paper has high feasibility. The classification characteristics of PPS sites are proposed for the first time, and PPS sites are divided into seven types according to three index dimensions: it provides the basis for differentiated decision making of PPS site selection.

The values and barriers of Building Information Modeling (BIM) implementation combination evaluation in smart building energy and efficiency

With the continuous increase in the number of buildings, the phenomenon of excessively high energy consumption becomes more and more serious. It is particularly important to reduce the energy consumption during the operation of the whole life cycle of the building. Building Information Modeling (BIM) technology is based on the relevant parameters of construction projects, and uses digital information simulation to establish building information models. It is one of the technical means of building energy consumption analysis and energy saving management, that can be explained as the main reason for stakeholders to guide energy and efficiency changes of the driving factor in buildings. We start co-occurrence statistics and type analysis based on the co-occurrence context analysis, construct the co-occurrence information that affects the values and barriers combination of BIM implementation for smart building energy and efficiency, and chose the expert database of the Green Construction and Intelligent Building Branch (GCIBB) of China Construction Association, that obtained 104 samples through modified snowball sampling, using exploratory factor analysis with factor load linear functions, and combined factor variance contribution rate weights. We created index function of the values and barriers combination of BIM implementation in smart building energy and efficiency, and classified and calculated the comprehensive score of each factor according to the ranking evaluation index, and mapped its practical significance. The results show that the 18 combined evaluation indicators proposed in this paper are suitable for evaluating the three elements of benefit, efficiency and quality of smart buildings, and can achieve continuous optimization of building energy consumption. The constructed multi-factor combination evaluation model, the extracted common factor variance cumulative contribution rate is greater than 80%.

Optimization of the Regulated Deficit Irrigation Strategy for Greenhouse Tomato Based on the Fuzzy Borda Model

It is of great significance to explore the strategy of regulated deficit irrigation (RDI) under mulched drip irrigation to stabilize tomato yield and improve quality and efficiency. This experimental study was conducted on a drip-irrigated greenhouse in two consecutive years (2020 and 2021). Three deficit levels were set for the flowering and fruit development stage (Stage I), and three were set for the fruit-ripening stage (Stage II). As a combination evaluation method, the fuzzy Borda model was used to optimize the RDI strategy of greenhouse tomato. The results showed that the net photosynthetic rate, stomatal conductance, transpiration rate, and total shoot biomass of tomato decreased with an increase in the water deficit, while the intercellular CO2 concentration had an opposite trend. The mild and moderate water deficit at Stage I reduced tomato yield by 16–24% and 30–40% compared to full irrigation. The water deficit at Stage II was able to improve various quality parameters and the water-use efficiency of tomato; the irrigation water-use efficiency (32.8–33.9 kg/m3) and leaf water-use efficiency (3.2–3.6 μmol/mmol) were the highest when the soil water content was 70–90% θf (field capacity) at Stage I and 40–60% θf at Stage II (T3). Based on the fuzzy Borda combination evaluation model, T3 was determined as the treatment with stable yield, high quality, and efficient irrigation under the experimental conditions. The irrigation regime was as follows: irrigating 20–25 mm in the transplanting stage, no irrigation in the seedling stage, irrigating 193.2–220.8 mm at Stage I, and then irrigating 27.6 mm at Stage II.