scholarly journals An Evaluation Model of Green Coal Supplier for Thermal Power Supply Chain Based on PCA-SVM

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Qian Zhang ◽  
Hai Shen ◽  
Yuanyuan Huo
Keyword(s):  
Supply Chain ◽  
Power Supply ◽  
Evaluation Model ◽  
Thermal Power ◽  
Principal Component ◽  
Calorific Value ◽  
Evaluation Index System ◽  
Support Vector ◽  
Supplier Evaluation ◽  
Evaluation Indexes

A thermal power supply chain differs from other supply chains in terms of supplier selection, materials transportation, products marketing, and so on. Therefore, the green coal supplier evaluation model has its own characteristics. Although many methods have been developed to solve the green supplier evaluation problem, little is known about how to evaluate the green coal supplier in the thermal power supply chain. To overcome this drawback, an evaluation index system for the green coal supplier is established, and new indexes such as price based on calorific value, quality indexes based on the designed coal type, and transportation indexes such as transportation carbon footprint and environment indexes are created according to the characteristic of the thermal power supply chain. Then, principal component analysis (PCA) is used to create the main evaluation indexes, and the support vector machine (SVM) is adopted for the evaluation model. Finally, a practical example is applied to show that the model established in this paper outperforms others in evaluation accuracy.

A Study on General Radar Equipment Supply Chain Based on Variable Weight Theory

2014 ◽  
Vol 543-547 ◽  
pp. 4358-4361
Author(s):  
Xiao Qiao Wen ◽  
Xiong Mei ◽  
Gui Xiang Li ◽  
Wei Qi ◽  
Jia Gen Jin
Keyword(s):  
Supply Chain ◽  
Hierarchical Structure ◽  
Index System ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Evaluation Indexes ◽  
Variable Weight

According to the principle of construction of the evaluation system, this paper established the corresponding evaluation indexes of the three aspects of equipment supply for user of universal radar equipment supporting: prepare, reserve, supply. There are 13 indexes. This paper establishes a set of index system more scientific, comprehensive, reasonable and hierarchical structure, and to conduct a comprehensive evaluation index system according to the method of AHP and variable weight fuzzy comprehensive assessment. In the end, this paper proves the rationality of index system and evaluation model.

scholarly journals Sustainable Supplier Evaluation and Selection of Fresh Agricultural Products Based on IFAHP-TODIM Model

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yupei Du ◽  
Di Zhang ◽  
Yue Zou
Keyword(s):  
Supply Chain ◽  
Evaluation Model ◽  
Multiple Attribute Decision Making ◽  
Agricultural Products ◽  
Evaluation Index System ◽  
Agricultural Product ◽  
Sustainable Supply Chain ◽  
Bottom Line ◽  
Multiple Attribute ◽  
Selection Of

In recent years, increasing pollution of the ecological environment, excessive use of pesticides, and lack of effective management of agricultural product supply chains have made the problem of having a green and safe supply of fresh food increasingly prominent. The sustainability of the fresh agricultural products supply has become an inevitable focus in the development of agricultural enterprises. There are some problems in the supply chain of fresh agricultural products, such as scattered production sites and difficult logistics transportation, which makes it difficult for enterprises to choose reliable suppliers. Supplier selection is a key component of sustainable supply chain management, and the criteria for evaluating the quality of sustainable suppliers are often affected by economic, social, and environmental factors. Therefore, from the perspective of sustainability, based on triple bottom line theory and comprehensively considering the three aspects of society, environment, and economy, this paper proposes a novel evaluation index system for the selection of sustainable suppliers of fresh agricultural products. This paper innovatively integrates the intuition fuzzy analytic hierarchy process and TODIM (an acronym in Portuguese of interactive and multiple attribute decision-making), and these are applied to select sustainable suppliers. Finally, the integration method is applied to the example, and a sensitivity analysis is carried out to verify the validity of the evaluation model.

scholarly journals Supplier Evaluation Model on SAP ERP Application using Machine Learning Algorithms

2018 ◽  
Vol 7 (2.28) ◽  
pp. 306
Author(s):  
Manu Kohli
Keyword(s):  
Machine Learning ◽  
Enterprise Resource Planning ◽  
Data Model ◽  
Evaluation Model ◽  
Learning Algorithms ◽  
Resource Planning ◽  
Information Management System ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Supplier Evaluation

For business enterprises, supplier evaluation is a mission critical process. On ERP (Enterprise Resource Planning) applications such as SAP, the supplier evaluation process is performed by configuring a linear score model, however this approach has a limited success. Therefore, author in this paper has proposed a two-stage supplier evaluation model by integrating data from SAP application and ML algorithms. In the first stage, author has applied data extraction algorithm on SAP application to build a data model comprising of relevant features. In the second stage, each instance in the data model is classified, on a rank of 1 to 6, based on the supplier performance measurements such as on-time, on quality and as promised quantity features. Thereafter, author has applied various machine learning algorithms on training sample with multi-classification objective to allow algorithm to learn supplier ranking classification. Encouraging test results were observed when learning algorithms,(DT) and Support Vector Machine (SVM), were tested with more than 98 percent accuracy on test data sets. The application of supplier evaluation model proposed in the paper can therefore be generalised to any other other information management system, not only limited to SAP, that manages Procure to Pay process.  

Intelligent online teaching system based on SVM algorithm and complex network

2020 ◽  
pp. 1-11
Author(s):  
Chuanxin Fang
Keyword(s):  
Online Teaching ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Research Work ◽  
Principal Component ◽  
Teaching Quality ◽  
Support Vector ◽  
School Teaching ◽  
The Impact ◽  
Quality Evaluation Model

English Online teaching quality evaluation refers to the process of using effective technical means to comprehensively collect, sort and analyze the teaching status and make value judgments to improve teaching activities and improve teaching quality. The research work of this paper is mainly around the design of teaching quality evaluation model based on machine learning theory and has done in-depth research on the preprocessing of evaluation indicators and the construction of support vector machine teaching quality evaluation model. Moreover, this study uses improved principal component analysis to reduce the dimensionality of the evaluation index, thus avoiding the impact of the overly complicated network model on the prediction effect. In addition, in order to verify that the model proposed in this study has more advantages in evaluating teaching quality than other shallow models, the parameters of the model are tuned, and a control experiment is designed to verify the performance of the model. The research results show that this research model has a certain effect on the evaluation of school teaching quality, and it can be applied to practice.

scholarly journals Supply chain finance credit risk assessment using support vector machine–based ensemble improved with noise elimination

2020 ◽  
Vol 16 (1) ◽  
pp. 155014772090363 ◽  
Author(s):  
Ying Liu ◽  
Lihua Huang
Keyword(s):  
Risk Assessment ◽  
Support Vector Machine ◽  
Supply Chain ◽  
Credit Risk ◽  
Financial Analysis ◽  
Learning Algorithm ◽  
Principal Component ◽  
Support Vector ◽  
Machine Model ◽  
Supply Chain Finance

Recently, support vector machines, a supervised learning algorithm, have been widely used in the scope of credit risk management. However, noise may increase the complexity of the algorithm building and destroy the performance of classifier. In our work, we propose an ensemble support vector machine model to solve the risk assessment of supply chain finance, combined with reducing noises method. The main characteristics of this approach include that (1) a novel noise filtering scheme that avoids the noisy examples based on fuzzy clustering and principal component analysis algorithm is proposed to remove both attribute noise and class noise to achieve an optimal clean set, and (2) support vector machine classifiers, based on the improved particle swarm optimization algorithm, are seen as component classifiers. Then, we obtained the final classification results by combining finally individual prediction through AdaBoosting algorithm on the new sample set. Some experiments are applied on supply chain financial analysis of China’s listed companies. Results indicate that the credit assessment accuracy can be increased by applying this approach.

scholarly journals Research on Dynamic Evolution Simulation and Sustainability Evaluation Model of China’s Power Supply and Demand System

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 2009
Author(s):  
Jin-peng Liu ◽  
Yu Tian ◽  
Hao Zheng ◽  
Tao Yi
Keyword(s):  
Power Supply ◽  
Evaluation Model ◽  
Supply And Demand ◽  
Interaction Mechanism ◽  
Principal Component ◽  
Demand System ◽  
Demand Systems ◽  
Evolution Simulation ◽  
Sustainability Problems ◽  
The Ideal

Power supply and demand systems are important support systems for industrial production and residents’ lives. They have multiple influencing factors, and complex mechanisms of interaction exist among these factors. In view of the present sustainability problems faced by China’s power supply and demand system, this research adopts a system dynamics (SD) model to simulate the evolution of China’s power supply and demand system, and analyzes the interaction mechanism of various elements of the system. Based on this, an innovative index system for the evaluation of the sustainability of power supply and demand systems is proposed based on the four elements of total amount, structure, technology and environment. Furthermore, by integrating Principal Component Analysis (PCA) and State Space (SS) method, a PCA-SS evaluation model is constructed to explore the development bottleneck of China’s power supply and demand system. The results show that there is still a large gap between the actual sustainability and the ideal range, and that the sustainability of structural and environmental layers needs further improvement. This research expands the knowledge system regarding the evaluation of the sustainability of power supply and demand systems and provides a theoretical reference for the optimization of China’s power supply and demand system.

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