Technique For Order Preference By Similarity To Ideal Solution Model Research Articles

Online Teaching Effect Evaluation and Analysis Using Combined Weighting Technique

An evaluation index system of online teaching satisfaction was established based on the data of a questionnaire survey. In addition, an evaluation index system of an online teaching effect with four first-level indexes and 14 second-level indexes was constructed from the aspects of pre-class preparation, video production, classroom teaching, and after-class guidance. Then, a combination weighting–Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model was established using the analytic hierarchy process (AHP), Criteria Importance Through Inter-criteria Correlation method, and TOPSIS model. The objective is to evaluate the online teaching effect of 10 engineering technology universities in Henan Province. Results show that the online teaching effect of these universities is generally satisfactory. In addition, video production and classroom teaching are important factors affecting online teaching, which, however, is slightly influenced by pre-class preparation. On this basis, this study proposes to enhance online assessment, improve students’ attention in class, strengthen teacher–student communication, actively perfect teaching resources, and create a good learning environment.

Study on the Effectiveness of the Integral Emergency Response System for Coal Mine Water Hazard Accidents Based on Combination Weighting

Improving the emergency response effectiveness of coal mines in response to water hazard accidents not only plays a vital part in minimizing the resultant losses, but also functions as an important index for evaluating the emergency response capability of coal mines. Therefore, it is of great necessity to test the emergency response capability of coal mines. In this study, an effectiveness measurement index system for the emergency response system that comprises two primary indexes (i.e., response capability and service capability) and six secondary indexes (i.e., accident information transmission, emergency command and control, emergency rescue and mitigation, emergency management, personnel team, and prevention and preparation) was constructed. Additionally, a technique for order preference by similarity to ideal solution (TOPSIS) model for evaluating the effectiveness of the integral emergency response system for coal mine water hazard accidents, based on combination weighting, was put forward. Both the empirical evaluation and model validation of the emergency response system for water hazard accidents were carried out by taking five coal mines attached to Henan Coking Coal Group as research objects. The findings suggest that the effectiveness of the emergency response system for water hazard accidents in the Guhanshan Coal Mine and the Zhongmachun Coal Mine is rated as “average”, while those in the Jiulishan Coal Mine, Zhaogu No. 1 Coal Mine, and Zhaogu No. 2 Coal Mine are graded as “good”. This result is consistent with the actual situation, which verifies the capacity of the proposed TOPSIS model to evaluate the emergency response system scientifically and efficiently for coal mine water hazard accidents. This study not only offers new ideas for how to enhance the comprehensive emergency response capability of coal mines with respect to water hazard accidents, but also provides support for making decisions concerning the upgrading of the emergency response capacity of coal mines.

Evaluating the Application Potential of Acid-Modified Cotton Straw Biochars in Alkaline Soils Based on Entropy Weight TOPSIS

As a good carbon source and soil conditioner, biochar is widely used in acidic soils but seldom in alkaline soils due to its high pH. In this study, cotton straw biochar was modified with five different acidic materials to obtain wood-vinegar- (WBC), monosodium-glutamate (MSG)-wastewater- (MBC), citric-acid- (CBC), phosphoric-acid- (PBC), and nitric-acid-modified biochars (NBC), and three dosages were used for each modifier. The pristine and modified biochars were characterized with scanning electron microscopy (SEM) and Fourier-transform infrared (FTIR) spectroscopy. The biochar properties such as pH, specific surface area (SSA), and elemental contents were measured. In addition, the technique for order preference by similarity to ideal solution (TOPSIS) model based on entropy weight was used to evaluate the application potential of the biochars in alkaline soils. The FTIR spectra showed that modification with the five acidic materials, MSG wastewater in particular, resulted in more oxygen-containing functional groups such as O-H, C=O, and C-O on the biochar surface. In addition, acid modification greatly decreased the pH: phosphoric acid modification significantly decreased the pH of cotton straw biochar by 5.71–7.88 units. For the same modifier, a higher dosage (i.e., a smaller biochar:modifier ratio) led to a larger decrease in the pH of cotton straw biochar. The magnitudes of increase in total soluble salt content followed the general order of CBCs > PBCs > WBCs > NBCs > MBCs. The SSA, average pore diameter, and total pore volume of biochar were changed as well. Modification using wood vinegar and MSG wastewater significantly decreased the SSA of cotton straw biochar by 15.58–16.24 m2 g−1 (82.7–86.2%) and 15.87–16.80 m2 g−1 (84.2–89.2%), respectively, whereas modification using citric acid and nitric acid significantly increased the SSA of cotton straw biochar by 4.51–4.66 m2 g−1 (23.9–24.7%) and 0.55–54.21 m2 g−1 (2.9–287.7%). The evaluation based on entropy weight TOPSIS model suggested that the MBCs have the highest potential for application in alkaline soils. This study presents a theoretical basis for evaluation of biochar application potential, demonstrates a way of improving biochar application potential, and provides a support for beneficial utilization of agricultural and industrial wastes such as cotton straw, wood vinegar, and MSG wastewater.

Performance appraisement of supplier selection in construction company with fuzzy AHP, Fuzzy TOPSIS, and DEA: A case study based approach

In the present marketing environment, choosing the right suppliers is very difficult for any construction company. Current supplier selection models in the construction industry often suffer from limitations such as incomplete criteria coverage, inadequate handling of uncertainties, and oversimplification of decision-making, leading to sub-optimal supplier choices and project risks. This paper aims in selecting the best suppliers among the different M-Sand environment suppliers. In this study 13 qualitative criterions are selected by the expert team. For handling the attributes, uncertainties, vagueness associated with supplier selection problems the Fuzzy Delphi, Fuzzy Analytical hierarchal Process (AHP) and Fuzzy Technique for order preference by similarity to ideal solution (TOPSIS) methods were chosen. In the first phase of this study, Fuzzy Delphi Method is employed to select the 5 significant criterions. These criterions can be used to help the construction company in the direction to choose the right suppliers at the end. During the second phase, one of the significant Multi-criteria Decision Making Method called AHP is employed with extended support of fuzzy logic to evaluate the weightage of each criterion. Further ranking of various alternative suppliers are done by Fuzzy TOPSIS model. The ranking results indicate that A2 is the best supplier followed by A1 and A2. The third phase of this study deals with analyzing both the qualitative and quantitative criteria, hence Data Envelopment Analysis (DEA) is adopted to correlate the criteria. This is done to select efficient suppliers. The develop model is demonstrated in the construction industry.

Application of TOPSIS model in active tectonic prioritization: Madeira watershed, South America

The Andes orogenic belt is one of the most tectonically active zones located between the convergent margins of the South American plate and the Pacific plate. From the dissected western belt to the expanded alluvial plain of Amazon basin, the Madeira watershed bears recent tectonic imprints. The tectonic signature is well documented by the spatial and linear characteristics of the five sub watersheds along with the Madeira trunk river and channels. The level of tectonic activeness has been assessed on the sub watersheds of the Madeira River, which is one of the main right-hand tributaries of the Amazon River. On the five defined sub-watersheds and the main channel watershed of Madeira, several morphometric indices, viz., asymmetry factor (AF), tilt angle (β), sinuosity index (SI), channel concavity (ɵ), elongation ratio (Re), circularity ratio (Rc), transverse topographic symmetry factor (T) and basin shape index (Bs), have been used. To rank the watersheds based on tectonic activity, we applied the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) The active tectonics was also tested by a comparative study of linear indicators as Hack profiles, longitudinal profiles and segment-wise stream gradient index (SL) of watersheds 2 (rank 1) and 3 (rank 6). The results reveal that the most tectonically active watershed 2 is located in a high seismic magnitude zone with several deep earthquake epicenters. The least tectonically active watershed 6 is located in a low seismic zone.

New evaluation method for the characterization of coatings by electroerosive alloying

The running-in coatings were formed on the surface of tin bronze QSn10-1 by electroerosive alloying (EEA) with soft antifriction materials such as silver, copper, Babbitt B83 and graphene oxide (GO). The mass transfer, surface roughness, coating thickness and dry friction coefficient of the running-in coatings were measured and analyzed by a precision electronic balance, three-dimensional optical profiler, metallographic microscope, scanning electron microscope (SEM), energy dispersive spectrometer (EDS) and friction and wear tester. An evaluation indicator system for the characterization was constructed based on six factors, including material price, time, mass transfer, roughness, thickness and friction coefficient of the coatings by electroerosive alloying. The Shannon entropy method was used to calculate the weight of different indices, and a comprehensive evaluation method for running-in coatings performance was proposed by combining the technique for order preference by similarity to ideal solution (TOPSIS) and a multicriteria decision-making technique. The TOPSIS model was employed for the comprehensive evaluation ranking of the characterization of the running-in coatings by electroerosive alloying.

Economic Evaluation of Drought Resistance Measures for Maize Seed Production Based on TOPSIS Model and Combination Weighting Optimization

In order to optimize the appropriate drought resistance measures in the implementation of high-efficiency and intensive production of maize seed, in 2018 and 2019, maize cultivation experiments with different drought resistance measures were carried out in the arid area of northwest China, including water retention agent (SA), white plastic film mulch (WF), black plastic film mulch (BF), straw mulch (SM), and open ground flat seed as control (CK). A total of five treatments were conducted. Ten specific indicators contained four types of attributes, namely the yield, quality, water use efficiency (WUE), and economic benefit of maize seed production, aimed at constructing a multilevel evaluation system. To improve the reliability of evaluation results, subjective and objective weights of indexes were calculated using the analytic hierarchy process (AHP) and entropy weight method (EWM), respectively. Then, based on the integrated weighting method of game theory (GT), the combined weights of subjective and objective unity were obtained. Finally, with the help of the technique for order preference by similarity to ideal solution (TOPSIS), a comprehensive benefit evaluation model was established to screen out the optimal drought resistance measures. Compared with CK, different drought resistance measures significantly improved the grain quality of seeds-production corn, and the average annual yield and WUE of black and white film treatments were improved by 49.57% and 42.97% and by 65.67% and 58.21%, respectively. This proved that black film mulching (BF) could significantly increase the yield and WUE of maize seed production and effectively improve grain quality, which could be used as the best drought-resistant cultivation mode for maize seed planting in Hexi and similar areas.

TOPSIS Model for evaluating the corporate environmental performance under intuitionistic fuzzy environment

With global resource waste and environmental pollution becoming increasingly serious, corporate environmental performance (CEP) has received much attention from researchers over the past decade. As an important part of economic development, enterprises also pay increasingly attention to environmental protection and pollution control. CEP is regarded as the result of corporate environmental management. Assessing CEP can not only make enterprises focus on the environmental protection and management, but also promote sustainable social development. And it is frequently viewed as a multi-attribute group decision-making (MAGDM) issue. Thus, a novel MAGDM method is needed to tackle it. Depending on the conventional TOPSIS (Technique for Order Preferenceby Similarity to Ideal Solution) method and intuitionistic fuzzy sets (IFSs), this essay design a novel intuitive distance based IF-TOPSIS method to assess CEP. First of all, a related literature review is conducted. What’s more, some necessary theories related to IFSs are briefly reviewed. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria is decided objectively by utilizing CRITIC method. Afterwards, relying on novel distance measures between IFNs, the conventional TOPSIS method is extended to the intuitionistic fuzzy environment to calculate assessment score of each enterprise. Eventually, an application about CEP evaluation and some comparative analysis have been given to demonstrate the superiority of the designed method. The results illustrate that the designed framework is useful for assessing CEP.

BMW-TOPSIS: A generalized TOPSIS model based on three-way decision

TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) uses a pair of a positive ideal solution and a negative ideal solution as two reference points to rank a set of decision alternatives. In some situations, a trade-off of the distances to the two extreme reference points may not necessarily be meaningful. Inspired by the theory of three-way decision as thinking in threes (e.g., two opposite poles and a third middle), in this paper we generalize the classical TOPSIS by adding a third middle reference point. We use a common setting for investigating systematically reference-point-based TOPSIS-style multi-criteria decision-making methods. In particular, we examine three classes of approaches: a) a best reference point based model (i.e., B-TOPSIS) and a worst reference point based model (i.e., W-TOPSIS), b) the classical best and worst reference points based model (i.e., BW-TOPSIS), and c) a new best, mean, and worst reference points based model (i.e., BMW-TOPSIS). The three classes are one-way TOPSIS, two-way TOPSIS, and three-way TOPSIS, respectively. Based on one-way and two-way TOPSISs, we give two specific methods of three-way TOPSIS. The experimental results, compared with the existing TOPSIS methods, show that the BMW-TOPSIS model is feasible and effective.

Assessing Efficiency of Urban Land Utilisation under Environmental Constraints in Yangtze River Delta, China.

Measuring the efficiency of construction land utilisation is important for optimising the allocation of regional resources and guiding the sustainable development of the regional society and economy. Based on municipal panel data on urban land use from 2009 to 2017 from a municipal perspective, this research built a slacks-based measure of a super-efficiency model (SE-SBM) to evaluate the temporal and spatial differentiation characteristics of the construction land-use efficiency of 41 cities in the Yangtze River Delta. Following this, the driving force of construction land efficiency was calculated using the Malmquist–Luenberger index. Finally, the entropy-weight TOPSIS (technique for order preference by similarity to ideal solution) model and the k-means clustering method were applied to evaluate an input–output model of the cities. The main conclusions are as follows: (1) The construction land efficiency of the Yangtze River Delta remains at a low level and presents a spatial differentiation pattern, with the efficiency being higher in the east and lower in the west. Due to undesired outputs, the mean value has dropped by 4.67%, and the regional imbalance has decreased. (2) The degree of efficiency loss is significantly positively correlated with the intensity of urban pollution emissions—the higher the pollution emissions, the greater the efficiency loss. (3) The total factor productivity of urban construction land is mainly driven by technological progress, while the promotion of technical efficiency is low and unstable. (4) The evaluation of construction land efficiency must include resource allocation or pollution emission factors to scientifically measure the input–output level. These research results will help to formulate reasonable land-use countermeasures.

Evaluation of subway passengers transfer hub congestion based on queuing model and TOPSIS method

To scientifically and reasonably evaluate and pre-warn the congestion degree of subway transfer hub, and effectively know the risk of subway passengers before the congestion time coming. We analyzed the passenger flow characteristics of various service facilities in the hub. The congested area of the subway passenger flow interchange hub is divided into queuing area and distribution area. The queuing area congestion evaluation model selects M/M/C and M/G/C based on queuing theory. The queuing model and the congestion evaluation model of the distribution area select the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. Queue length and waiting time are selected as the evaluation indicators of congestion in the queuing area, and passenger flow, passenger flow density and walking speed are selected as the evaluation indicators of congestion in the distribution area. And then, K-means cluster analysis method is used to analyze the sample data, and based on the selected evaluation indicators and the evaluation model establishes the queuing model of the queuing area and the TOPSIS model of the collection and distribution area. The standard value of the congestion level of various service facilities and the congestion level value of each service facility obtained from the evaluation are used as input to comprehensively evaluate the overall congestion degree of the subway interchange hub. Finally we take the Xi’an Road subway interchange hub in Dalian as empirical research, the data needed for congestion evaluation was obtained through field observations and questionnaires, and the congestion degree of the queue area and the distribution area at different times of the workday was evaluated, and the congestion of each service facility was evaluated. The grade value is used as input, and the TOPSIS method is used to evaluate the degree of congestion in the subway interchange hub, which is consistent with the results of passenger congestion in the questionnaire, which verifies the feasibility of the evaluation model and method.

Economic, Social, and Ecological Impact Evaluation of Traffic Network in Beijing–Tianjin–Hebei Urban Agglomeration Based on the Entropy Weight TOPSIS Method

In recent years, with the rapid development of urban transportation network in China, many problems have been exposed, especially in the Beijing–Tianjin–Hebei (BTH) region. Under the call of sustainable development, it is of great significance to evaluate the economic, social, and ecological (ESE) impact of transportation network in BTH urban agglomeration for promoting the sustainable development of transportation ESE in BTH urban agglomeration. In this paper, 12 indicators in the field of transportation are selected to build the evaluation index system of ESE effects of transportation network in BTH urban agglomeration. By using entropy weight TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) model and the Jenks natural breaks classification method, the ESE impacts of transportation network in 13 cities of BTH from 2013 to 2017 are analyzed from the temporal and spatial dimensions. The research shows that: (1) From 2013 to 2017, the economic impact degree of traffic network shows an annual fluctuation trend, the social impact degree increases year by year, and the ecological impact degree decreases year by year; (2) For the cities of BTH, the ESE impact assessment results of transportation network from 2013 to 2017 can be divided into seven clusters. Except Handan City, the ESE impact assessment categories of other cities’ transportation network have been improved, but the proportion of cities in the transition period is still large, especially the “Low-Low-Low” cities. The types of cities in the transitional period need to be focused. It is still a heavy burden to realize the ESE coordination and sustainable development of BTH urban agglomeration transportation network.

Erosion susceptibility mapping of sub-watersheds for management prioritization using MCDM-based ensemble approach

Soil erosion (SE) creates several environmental problems in fragile tropical watersheds, such as channel degradation, reservoir sedimentation, and flash flood. Therefore, identification of erosion susceptible areas at the sub-watershed level is necessary for the sustainable management of available resources. Previous studies on sub-watershed prioritization are based on a particular method, which leads to uncertainty because other methods may produce different results. Therefore, in the present work, a novel MCDM (multi-criteria decision-making)–based ensemble approach has been used for the prioritization of sub-watersheds of the Dwarkeswar River basin. Five MCDM models were used in the present study, namely simple additive weighting (SAW), complex proportional assessment (COPRAS), additive ratio assessment (ARAS), technique for order preference by similarity to ideal solution (TOPSIS), and multi-objective optimization on the basis of ratio analysis (MOORA). The non-parametric Spearman rank correlation method was used to determine the best model and measure the degree of similarity among the results obtained from different models. Rank correlation indicated that the COPRAS model has the highest accuracy in the prediction of erosion susceptibility. But the final ranks were given to the sub-watersheds by averaging the ranks obtained from different MCDM models. The TOPSIS model was not included for averaging because TOPSIS shows a negative correlation with the SAW (− 0.082) and ARAS (− 0.179) models and a very low positive correlation with the COPRAS (0.181) model. This combined ensemble method placed sub-watersheds 10 and 11 in first and second ranks, respectively, on the basis of susceptibility to SE.

An empirical evaluation on the performance of food service industry in Malaysia with TOPSIS model

The food service industry makes impacts on society and plays a key role in expanding economic and business opportunity. Besides that, the economic sector is also contributed by the food and beverage industry. Therefore, performance evaluation is vital for the food service industry in a highly competitive environment in order to improve the decision-making process in an organization. The objective of this study is to propose a conceptual framework in evaluating and ranking the financial performance of the food companies from the consumer products sector in Malaysia with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. Current ratio, return on equity, profit margin, debt to equity ratio, earnings per share, dividend yield and price earnings ratio are the financial ratios employed in this study. The results of this study show that HEXZA gives the highest performance, followed by TGUAN, 3A and finally CANONE. This study is significant as it helps to evaluate the financial performance of food service industry in Malaysia with the proposed conceptual framework using TOPSIS model.

Monitoring and Prediction of Dust and Investigating its Environmental Impacts in the Western Half of Iran and the Eastern Borders of Turkey and Iraq, Using Remote Sensing and GIS

In recent years, the damage caused by dust in different parts has increased dramatically. There are many dusty areas around the world. One of these regions in the southwest of Asia is Iran. The purpose of this study is to model and predict the hazardous dust phenomenon in dusty regions of Iran. For this purpose, dust data from 28 stations of intense dusty areas in Iran were collected at 29-year time intervals. Then, adaptive-network-based fuzzy inference systems (ANFIS) and the core of the radial base function (RBF) models were used for modelling and then the two models were compared to the future exact prediction. Finally, the dust data for all stations are prioritized using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multivariate decision-making model and output data are mapped by ArcGIS software. According to the results of this study, RMSE of the ANFIS model was 10.5 and the RBF model was 2.18. Therefore, the accuracy of RBF was more than the ANFIS model for prediction of the dust simulated in years, so the RBF model was used to predict. Based on the dust data obtained from the output of the RBF model in both the mean and maximum of dust abundance, the western and southwestern stations of the study areas were more exposed to dust in the future. Also, according to TOPSIS model, in the prioritization of stations involved with dust for simulated years, Abadan, Masjed Soleyman and Ahwaz were ranked by the amount of 100, 95% and 81%, respectively. Dust is one of the atmospheric phenomena that have adverse environmental effects and consequences. Dust storms have detrimental effects on the health and economy of society and climate change. Understanding the nature, origin and effects of dust storms plays an important role in determining its control methods.

Study of the Allocation of Regional Flood Drainage Rights in Watershed Based on Entropy Weight TOPSIS Model: A Case Study of the Jiangsu Section of the Huaihe River, China

During the flood season, various regions in a watershed often have flood drainage conflicts, when the regions compete for flood drainage rights (FDR). In order to solve this problem, it is very necessary to study the allocation of FDR among various regions in the watershed. Firstly, this paper takes fairness, efficiency and sustainable development as the allocation principles, and comprehensively considers the differences of natural factors, social development factors, economic development factors and ecological environment factors in various regions. Then, an indicator system for allocation of FDR among regions in the watershed is established. Secondly, an entropy weight Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model is used to construct the FDR allocation model among regions in the watershed. Based on a harmony evaluation model, a harmony evaluation and comparison are carried out on the FDR allocation schemes under three different allocation principles. Finally, taking the Jiangsu section of the Huaihe River watershed as an example, the FDR of eight cities in the watershed are allocated and evaluated to see if the allocation scheme is harmonious. The results show that the allocation scheme of FDR based on the principles of fairness, efficiency and sustainable development has the highest degree of harmony, which can meet the FDR demands in various regions in the watershed, avoid the occurrence of flood drainage conflicts among regions, form an orderly flood drainage situation and promote the harmonious development of the watershed.

Optimum prioritisation of sub-watersheds based on erosion-susceptible zones through modeling and GIS techniques

The priority assessment of erosion-susceptible zone in a drainage basin is an important approach to diminish various environmental threats related to soil erosion. In a large drainage basin, management and conservation of the entire area at an optimum level are sometimes inefficient due to lack of human resources and financial strength. Therefore, it is prerequisite to establish a viable technique for prioritisation of sub-watersheds in such way that ensures sustainability and high productivity of the region. The objective of this study is to identify erosion-susceptible areas within the sub-watersheds of Mayurakshi river basin located in a transitional zone between Chotanagpur Plateau and Bengal Basin where the risk of soil erosion is very much noticeable. The whole basin has been divided into number of sub-watersheds (SW), and a set of drainage morphometric parameters have been used to identify the potentiality of erosion. Finally, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model has been implemented to prioritise the critical areas for better management strategy. This method specifically considered the interdependencies of all criteria for which it has been very much applicable for the assessment of erosion risk zones. The output of TOPSIS model reveals SW6 and SW11 have been fall under high- and low-erosion-susceptible zones, respectively. To validate the output of the model, rainfall erodibility index (R factor) has been calculated which shows that the same watershed (SW6) has been fall under high rainfall erosivity zone depicting the need of prioritisation at an earliest convenience.

A New Evaluation Method for Slope Stability Based on TOPSIS and MCS

Slope evaluation is a basic geotechnical engineering issue. The rationality of index weight greatly affects the accuracy of evaluation results in the evaluation system. Furthermore, in practical engineering, some indexes can be considered random variables obeying a certain distribution. Traditional evaluation methods of slope stability ignore the effect of this index uncertainty. Therefore, it is necessary to obtain the evaluation results of slope stability reasonably by modifying the previous weighting methods and considering the uncertainty values of the indexes. A new method has been introduced to solve the problem mentioned previously based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Monte Carlo simulation (MCS). TOPSIS is used as a basic model for evaluating slope stability. TOPSIS and MCS are coupled to establish multiobjective optimization simulation model, which can search the more optimal and reliable weight. The optimal weight is then substituted into the TOPSIS basic model to calculate the status of slope stability. In this calculation process, MCS is introduced into the TOPSIS basic model to consider the uncertainty value of index. The new method of evaluating slope stability was demonstrated by taking a practical project as an example. Compared with other weighting methods, the coupled TOPSIS and MCS model can obtain the most reliable weight, and the reliability is 48.7%. Then, the evaluation of slope stability was examined with the certainty and uncertainty cases, respectively. The results demonstrate that the proposed new evaluation method is more realistic than the traditional methods for evaluating the slope stability. The new method has high accuracy and is easy to use.

Examining the Urban and Rural Healthcare Progress in Big Cities of China: Analysis of Monitoring Data in Dalian from 2008 to 2017.

How to effectively reduce the disparity between urban and rural medical healthcare has become a major global concern. In China, the government has issued a series of reform measures to address the gap between urban and rural medical care. To explore the impact of China’s medical system reforms in improving health services in urban and rural areas and understand the factors promoting and hindering progress, we evaluated the healthcare system in Dalian City, China, from 2008 to 2017. The weighted TOPSIS (technique for order preference by similarity to ideal solution) model was used to assess the development of the healthcare system in the different districts and employed the obstacle model to identify and analyze indicators that hinder progress in health services. Using the local spatial clustering function, we categorized the districts in terms of the hindrance type that significantly hamper the growth of the healthcare system. Our results show the healthcare system in Dalian’s urban areas has steadily increased, while development in rural areas has been erratic. Although the urban–rural healthcare disparity has narrowed distinctly, sustained progress is not guaranteed. Based on the location theory, residents in urban areas are more affected by economic factors, while those in rural areas are more influenced by time considerations. When initiating healthcare reforms in urban areas, the impact of varying land prices and per capita disposable income should be considered. For rural areas, constructing more medical institutions to reduce the impact of time costs should be considered. We also found different factors that hinder the growth of the healthcare system for urban and rural areas. To address these impediments to progress, urban areas should pay more attention to coordinated development, while rural areas should address specific concerns based on local needs and conditions. More research on the progress in medical reform is crucial to provide reference and policy-guidance for countries facing similar concerns.

Evaluation of Recent Advanced Soft Computing Techniques for Gully Erosion Susceptibility Mapping: A Comparative Study.

Gully erosion is a problem; therefore, it must be predicted using highly accurate predictive models to avoid losses caused by gully development and to guarantee sustainable development. This research investigates the predictive performance of seven multiple-criteria decision-making (MCDM), statistical, and machine learning (ML)-based models and their ensembles for gully erosion susceptibility mapping (GESM). A case study of the Dasjard River watershed, Iran uses a database of 306 gully head cuts and 15 conditioning factors. The database was divided 70:30 to train and verify the models. Their performance was assessed with the area under prediction rate curve (AUPRC), the area under success rate curve (AUSRC), accuracy, and kappa. Results show that slope is key to gully formation. The maximum entropy (ME) ML model has the best performance (AUSRC = 0.947, AUPRC = 0.948, accuracy = 0.849 and kappa = 0.699). The second best is the random forest (RF) model (AUSRC = 0.965, AUPRC = 0.932, accuracy = 0.812 and kappa = 0.624). By contrast, the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) model was the least effective (AUSRC = 0.871, AUPRC = 0.867, accuracy = 0.758 and kappa = 0.516). RF increased the performance of statistical index (SI) and frequency ratio (FR) statistical models. Furthermore, the combination of a generalized linear model (GLM), and functional data analysis (FDA) improved their performances. The results demonstrate that a combination of geographic information systems (GIS) with remote sensing (RS)-based ML models can successfully map gully erosion susceptibility, particularly in low-income and developing regions. This method can aid the analyses and decisions of natural resources managers and local planners to reduce damages by focusing attention and resources on areas prone to the worst and most damaging gully erosion.