Information Entropy Weight Method Research Articles

The Analysis of Transit Oriented Development (TOD) of Electric Train Stations in Bangkok and Metropolitan Region: The Case Study of Chaleom Ratchamongkon Line and Chalong Ratchadham Line

This research studies transit oriented development (TOD) of two Metropolitan Rapid Transit (MRT) lines, Chaloem Ratchamongkon Line (Blue line) and Chalong Ratchatham line (Purple line), total 53 stations in total, in Bangkok and Nonthaburi Province. The researcher analyze four factors of built environment around mass transit station, 1) Density 2) Diversity 3) Design and Distance 4) Destination and Connectivity. For the density factors, including population density, number of points of interest (POI) and total building area to land area ratio (FAR). For the diversity factors, including the diversity of land use and number of shops around the station. For design and distance factors, including road density, number of parking spaces, Open Space Ratio (OSR). As for the factors related to destinations and connectivity, including the number of bus lines, number of entrances and exits of the train station, number of schools, Number of condominiums and number of villages. The researchers have considered the weight of each variable by using the Information entropy weight method (IEW) and calculated the transit oriented development score (TOD SCORE). From the TOD SCORE calculations of all 53 stations, the researchers find the strengths and weaknesses of each station. The average TOD score of the Purple Line stations is higher than that of the Blue Line stations. The station with the highest total TOD SCORE on the Blue Line is Tha Phra Station and the station with the highest total TOD SCORE on the Purple Line is Sai Ma Station. The station with the lowest total TOD SCORE on the Blue Line is Bang Sue Station and the station with the lowest total TOD SCORE on the Purple Line is Bang Rak Noi Tha It Station. In addition, the researchers analyzed the maximum and minimum values of TOD SCORE for each factor. and described in this research. The results of TOD SCORE analysis can analyze the strengths and weaknesses of each station and determine the development guidelines of mass transit stations in the future using a station with a high TOD SCORE as a model for development of the mass transit system in the future.

A quantitative enhanced assessment for ancient landslide reactivation risk considering cross-time scale joint response mechanism

Ancient landslide has strong concealment and disturbance sensitivity due to its special geotechnical mechanical characteristics, and it is the potential hazard that cannot be ignored in human activities and major engineering planning. The quantitative assessment of ancient landslide reactivation risk has become more necessary for pre-disaster scientific warning. However, because the mechanisms of deformation and damage during the evolution of ancient landslides are quite complex, traditional landslide risk assessment methods only select the single-time scale and relatively stable environmental factors for analysis, lacking consideration of dynamic triggering factors such as rainfall. Focusing on the complexity, a quantitative enhanced assessment for ancient landslide reactivation risk considering cross-time scale joint response mechanism is proposed. First, on the basis of systematic analysis of the implicit genesis mechanism and explicit characterization, an evaluation system of the cross-time scale joint characteristics of ancient landslide reactivation is constructed. Then, XGBoost algorithm and SBAS-InSAR are used to establish the long-time scale developmental evolution mechanism model and the short-time scale dynamical trigger model, respectively. Subsequently, we propose a cross-time scale joint response mechanism. The information entropy weight method is applied to calculate the contribution degree of long-short time scale assessment models for ancient landslide reactivation based on the constraints of quantitative interval thresholds, and the assessment processes of different time scales are dynamically and quantitatively correlated. Finally, the updated optimization of the assessment of ancient landslide reactivation risk is achieved. In this research, experimental analysis was carried out for ancient landslide groups in a geological hazard-prone area in Fengjie County, Chongqing, a typical mountainous region of China. The results of the comparative analysis validate the superiority of the method in this paper. It helps to accurately assess the ancient landslide potential hazard in advance, providing scientific basis and technical support for the risk assessment of mountainous watershed geological hazards and major engineering projects.

Multivariate State Estimation Technique Combined with Modified Information Entropy Weight Method for Steam Turbine Energy Efficiency Monitoring Study

An energy efficiency monitoring method of the steam turbine system is studied in this paper. Multivariate state estimation technique (MSET) is utilized to compare the actual monitoring parameters and the healthy data of the equipment in normal working condition with a multi parameter estimation model. Due to the limitation of a single heat rate index in evaluating energy efficiency variation, the energy efficiency deviation degree combined with improved information entropy weight is proposed to judge the steam turbine’s operation condition levels. The index value in the modified weight method has been searched for more steady weight values calculated by information entropy values with small variation. Taking a 600 MW unit as an example, the energy efficiency levels of the unit under a 550 MW normal working condition are clustered into four groups, testifying the MSET model correctness and calculating the deviation degree value. Then, the energy efficiency status monitoring model is utilized to record residuals of actual data and estimated data during abnormal energy efficiency period. The residuals over deviation degree are then marked and judged as related with the abnormal data. The results show that the MSET model can timely and accurately judge the change of unit operation state, and the deviation degree calculated by the modified information entropy weight method can provide earlier warnings for the abnormal energy efficiency working conditions.

Smart Supply Chain Risk Assessment in Intelligent Manufacturing

ABSTRACT This paper identifies risk factors in the smart supply chain and develops a risk assessment index system for reducing potential losses in intelligent manufacturing. Specifically, based on the supply chain operation reference theory, we investigate the performance indicators and characteristics of the smart supply chain in intelligent manufacturing in China. A conceptual model for identifying risks of the smart supply chain is developed, and a questionnaire is designed to measure the risks of the smart supply chain in intelligent manufacturing. Using the hierarchical clustering analysis, an improved risk assessment model is derived with 22 risk factors based on 814 valid sample data. Moreover, the information entropy weight method is used to compute the risk weights for the smart supply chain in intelligent manufacturing. The risk weights are further verified by simulation and proved that these risk factors and risk weights have high practical efficiency. Theoretical and practical implications are also presented.

Utilization of bark waste of Acacia mangium: The preparation of activated carbon and adsorption of phenolic wastewater

After the extraction of industrial tannins from Acacia mangium, there is a lot of bark waste. Thus, we use these bark wastes to produce activated carbon using the phosphoric acid activation method. The information entropy weight method is employed to select the best process according to the weight coefficients of the activated carbon yield and value of methylene blue adsorption. In this study, the phenol adsorption behaviors of activated carbon and its thermodynamic and kinetic characteristics are investigated. The results indicate that the best process for the preparation of activated carbon from the bark waste of Acacia mangium involves phosphoric acid concentration of 50 %, carbonization temperature of 500°C, and carbonization time of 90 min. Under these conditions, activated carbon obtained from the bark waste of Acacia mangium in this study is 53.04 %, and the value of methylene blue adsorption is 6.0 mL/0.1 g. In liquid, the adsorption capacity of activated carbon increases with the initial content of phenol, and the highest value is around 96.92 mg g−1, which is obtained at 25°C. The adsorption thermodynamic is well expressed by the Freundlich isotherm adsorption equation, and the adsorption behavior curves flow McKay second-order adsorption kinetic equation. This result indicates that phenol wastewater is absorbed very well by activated carbon prepared from the bark waste of Acacia mangium. This study lays the foundation for further development of biomass-activated carbon strategy and provides a promising insight into the enhancement utilization of Acacia mangium.

A Novel Node Flexibility Evaluation Method of Active Distribution Network for SNOP Integration

With the rising penetration levels of random resources such as renewable energy (RE) and electric vehicles (EVs), the uncertainty of active distribution network (ADN) is inherently increasing. To deal with disturbances and enhance stable operation, many power electronic devices such as Soft Normally Open Point (SNOP) have been integrated to ADN. This paper proposes a novel node flexibility evaluation method of ADN for SNOP integration. Firstly, operation scenarios of ADN are generated based on the k-medoids and k-means clustering method. A hybrid algorithm based on particle swarm optimization (PSO) and simulated annealing (SA) is used in the scenarios. The above is the demand assessment for the flexibility evaluation. Then, RE consumption, load satisfaction, voltage deviation and netload fluctuation of each node are obtained from scenarios and weighted by the information entropy weight method (EWM) to form the comprehensive flexibility index. Nodes are classified according to the evaluation results, which provide the integrated location of SNOP. Finally, a case study showed the differences between the proposed method and others.

The Coupling Coordination Relationship between Tourism Competitiveness and Economic Growth of Developing Countries

On the basis of the coupling coordination degree (CCD) model and information entropy weight method, this study examined the relationship between tourism competitiveness and economic growth of 56 developing countries from 2008 to 2017. The results show that: (1) the overall status of the CCD between tourism competitiveness and economic growth was in a state of unbalance that was mainly caused by the lag of economic growth, which demonstrates the important contribution of tourism in developing regions. (2) the CCD has been gradually improving since 2008, and the differences amongst the CCDs of developing countries have been shrinking and (3) the spatial distribution of the CCD between tourism competitiveness and economic growth has heterogeneity. Latin America & the Caribbean, and East Asia & the Pacific have the highest CCD, whereas Sub-Saharan Africa witnessed severely unbalanced development between tourism competitiveness and economic growth in 2008–2017.

Comprehensive Evaluation of Sustainable Development of Real Estate Industry Based on Information Entropy Weight Method

Under the conditions of market economy, the healthy development of the real estate market is of great significance to the normal operation of the real estate economy and the sustainable development of the real estate economy. Therefore, it is necessary to be able to accurately evaluate the development of the real estate industry and adopt appropriate macro-control measures in time. Taking Xiamen as an example, this paper adopts the way to combine objective information entropy weight method with subjective order relationship analysis method to determine the weight of group decision makers on program attributes and balance the importance of each index. According to the comprehensive attribute value of each scheme, the weight of decision makers is calculated by using entropy weight method for giving the evaluation result of the scheme. The results show that the overall situation of the development of real estate industry in Xiamen is more optimistic, and the weight of each index after the normalization of land transfer price is the highest. Based on the research conclusions, this paper proposes corresponding assessment commendations as a reference for relevant parties.

Study on service selection effort estimation in service oriented architecture‐based applications powered by information entropy weight fuzzy comprehensive evaluation model

Service selection is a very challenging core task in service oriented architecture-based application (SOABA) development. Service selection is based on user's business need and budget available. A large amount of effort is invested in selecting the most preferred service from a pool of similar services available in the market by various service providers. To propose a direction for solving the problem of service selection effort (SSE) estimation in SOABA is the objective in this study. An algorithm for SSE estimation powered by information entropy weight (IEW) fuzzy comprehensive evaluation model is presented in this study wherein the synthesis performance of each candidate service is evaluated to select the most preferred service. Larger the synthesis performance of a candidate service, higher the chances of its selection and less will be the effort invested. An empirical study is presented that assess the 24 significant parameters that affect SSE estimation by using proposed algorithm. This approach is comprehensible and rational and well suited for SOABA. The results obtained via this proposed method suggest its applicability and usefulness for real-world applications. The proposed work also explains why IEW method is useful for SSE estimation along with the research gap in existing common evaluation methods.

Evaluating Tourist Destination Performance: Expanding the Sustainability Concept

Performance evaluations are a critical tool in promoting the sustainability of tourist destinations. The literature shows a lack of consensus on basic terminology and definitions of destination performance. While research focuses on business efficiency, areas such as development effectiveness, social equality, and environmental integrity are still not well understood, even though these are salient elements of sustainable development. This paper provides a framework for evaluating destination performance under the 4E rubric of economy, efficiency, effectiveness, and environmental quality, which reflects a more holistic and effective destination performance. The information entropy weight method and a multi-factor comprehensive evaluation model are developed and applied to an international destination, Zhangjiajie, China, which was selected as a case study to test the framework developed. Results show that the economy, efficiency, effectiveness, and environmental quality aspects should be considered when evaluating tourism development performance. The empirical analysis shows that based on these criteria, Zhangjiajie’s destination performance improved measurably during the test period from 2005 to 2009. The results indicate that significant events, natural disasters, and financial crises influence performance most.

Lake health assessment method based on the coordinated development degree of ecology and social service function

本文首先运用频度分析法构建湖泊生态系统健康评价指标体系；其次，应用变异系数法与信息熵权法相结合的组合赋权法计算指标权重；在此基础上提出了基于生态-社会服务功能协调发展度的湖泊生态系统健康评价方法，并给出从湖泊综合发展水平和湖泊协调发展度两方面度量湖泊生态系统健康水平的等级划分标准.应用此评价方法，以白洋淀生态系统为研究对象，开展其健康状况及协调发展状况的模型实证研究.结果显示：白洋淀生态系统综合发展水平处于不健康病态萎缩状态，湖泊协调发展度属于临界协调发展.该方法综合考虑了生态完整性和社会服务功能两个方面的协调性和发展性进行湖泊健康评价，从协调、发展的角度为湖泊管理建设提供建议.同时研究表明协调发展度湖泊健康评价法具有计算简单、适用性强的特点，同样适用于其他湖泊健康评价.;In this paper, the lake ecosystem health evaluation index system was established using the frequency analysis method. Then, the weights of the index were calculated by the Combination Assigning Method combined Variation Coefficient Method with the Information Entropy Weight Method. Finally, the evaluation method of the lake ecosystem health was proposed based on the coordinated development degree of ecological-social service function. In addition, the classification standard of the lake ecosystem health level was given out from the aspects of lake comprehensive development level and lake coordinated development degree. Based on this evaluation method, Lake Baiyangdian ecosystem was used as the research object to carry out the empirical study on the health status and the coordinated development degree. The results show that the comprehensive development level of Lake Baiyangdian ecosystem is in the state of unhealthy morbid state, and the coordinated development degree belongs to the critical coordinated development. This method takes the coordination and development of ecological integrity and social service function into consideration while evaluating lake health, and provides suggestions for lake management construction from the point view of coordination and development.

Entropy weight-set pair analysis based on tracer techniques for dam leakage investigation

With the rapid development of industry and projects for ensuring the amounts of water that those industries require, the capacities and scales of hydraulic structures including reservoirs, dams, and weirs have increased sharply. Numerous dams experience some seepage, when water is held behind them; thus, dam leakage detection has been and continues to be a major concern. The basic task involves finding the path of the leakage, especially the concentrated leakage path. Using tracer techniques, we treat dam leaks as multiple attribute evaluation problems, which is one innovation presented in this paper. Entropy weight-set pair analysis, a new method of identifying leaks, is introduced. The water samples and the information flows including conductivity, pH, Cl−, D, and 18O are set as alternatives and indexes, respectively. Then, the connection degree is calculated according to set pair analysis, followed by the weight of each index using an information entropy weight method based on the principle of maximum entropy. Finally, the integrated degree of connection of all the samples is calculated, to provide a basis for classifying water samples and judging the adequacy of the water resources. To verify the validity and feasibility of this proposed model, the Ling’ao reservoir, which is situated in Guangdong province of China’s southeastern monsoon zone and notable for its particularly heavy seepage is taken as a case study. The results indicate that the model is suitable for objectively analyzing dam seepage problems, especially given that the results match those obtained for the horizontal velocity as measured with drillings and the temperature distribution across the dam body.

Entropy weight-set pair analysis (SPA) for dam leakage detection

The dam seepage flow contains many kinds of materials, forming the information flow, the information entropy of which can be used to determine the nature of the flow field; and the water chemistry and environmental isotope detection methods have been widely applied. Based on the knowledge of information entropy and set pair analysis, a new method consisting of water chemistry and environmental isotope detection, entropy weight-set pair analysis model, is introduced to ascertain the dam concentration leakage channels. Firstly, PH, conductance, Cl, δD and δO are chosen as five detection indexes, and the connection degree of each index value to the classification standard is calculated. Then, the weight of each index is determined by using the information entropy weight method based on the principle of the maximum entropy. After that, the comprehensive connection degree of all samples from the drilling is calculated, and thus all the samples are classified so as to determine the resource of water. Finally, this new method is applied to detect the dam leakage channels of one south reservoir and the results are tested and improved by the method of horizontal velocity and temperature detection. It is concluded that the results of the entropy weight-set pair analysis model match those of the horizontal velocity and temperature detection very well.