BRT Signal Priority Control Strategy Model Based on Travel Social Benefits

ICTE 2015 ◽  
2015 ◽  
Author(s):  
Yuhang Ba ◽  
Hongguo Shi ◽  
Zizheng Guo
Keyword(s):  
Control Strategy ◽  
Social Benefits ◽  
Model Based ◽  
Strategy Model

scholarly journals Analysis of Internet Financial Risk Control Model Based on Machine Learning Algorithms

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Mingjin Liu ◽  
Ruijie Gao ◽  
Wei Fu
Keyword(s):  
Machine Learning ◽  
Credit Risk ◽  
Empirical Analysis ◽  
Influencing Factors ◽  
Early Warning ◽  
Control Strategy ◽  
Risk Control ◽  
Consumer Finance ◽  
Model Based ◽  
Strategy Model

On the basis of traditional credit risk control, this paper proposes the demand and direction of a new credit risk control strategy based on machine learning and relying on big data. First, on the basis of introducing the basic algorithmic principles of machine learning, we give reasons for choosing machine learning models and build a machine learning-based Internet consumer finance credit risk control strategy model to provide theoretical support for the empirical analysis later. Second, we take the test data of Internet consumer finance S company as the research sample and carry out empirical analysis according to the machine learning-based Internet consumer finance credit risk control strategy model. The comparison of the training results is based on the comprehensive consideration of training time, validation set accuracy, TPR evaluation indicators, and interpretability of the results; it verifies the advantages of the machine learning model in screening the key influencing factors that cause the overdue performance of credit customers. According to the optimized credit risk control strategy, corresponding strategy suggestions are provided for the credit risk control of S company. The research results show that the prediction effect of the classification model based on traditional linear regression is generally lower than that of the model based on the classification algorithm based on machine learning, and there is a complex nonlinear relationship between platform default and its related influencing factors. The accuracy of classification and early warning results of the random forest algorithm is relatively high, and the detection rate of the decision tree model is relatively high, but the cost is also the highest. In addition, the accuracy of the four types of early warning models is relatively stable, reaching an average of 80%. This paper proposes a machine learning-based Internet consumer finance credit risk control strategy model. Its system, timeliness, and risk prediction capabilities provide new ideas and suggestions for Internet consumer finance companies to design risk control strategies.

Human operator control strategy model

1980 ◽  
Author(s):  
Harold F. Engler ◽  
Esther L. Davenport ◽  
Joanne Green ◽  
William E. Sears
Keyword(s):  
Control Strategy ◽  
Human Operator ◽  
Strategy Model ◽  
Operator Control

Optimal control strategy for cancer remission using combinatorial therapy: A mathematical model-based approach

2021 ◽  
Vol 145 ◽  
pp. 110789
Author(s):  
Parthasakha Das ◽  
Samhita Das ◽  
Pritha Das ◽  
Fathalla A. Rihan ◽  
Muhammet Uzuntarla ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Optimal Control ◽  
Control Strategy ◽  
Optimal Control Strategy ◽  
Combinatorial Therapy ◽  
Model Based ◽  
Cancer Remission

A numerical and experimental study of a simple model-based predictive control strategy in a perimeter zone with phase change material

2018 ◽  
Vol 24 (9) ◽  
pp. 933-944 ◽  
Author(s):  
Anastasios C. Papachristou ◽  
Charalampos A. Vallianos ◽  
Vasken Dermardiros ◽  
Andreas K. Athienitis ◽  
JosÉ A. Candanedo
Keyword(s):  
Experimental Study ◽  
Simple Model ◽  
Phase Change ◽  
Phase Change Material ◽  
Predictive Control ◽  
Control Strategy ◽  
Model Based ◽  
Change Material

Model Based Design and Optimization for Large Bore Engines: Some Industrial Case Studies

2017 ◽  
Author(s):  
Prashant Srinivasan ◽  
Sanketh Bhat ◽  
Manthram Sivasubramaniam ◽  
Ravi Methekar ◽  
Maruthi Devarakonda ◽  
...  
Keyword(s):  
System Design ◽  
Case Studies ◽  
Control Strategy ◽  
Internal Combustion Engines ◽  
Cost Optimization ◽  
Engine Performance ◽  
Design And Optimization ◽  
Model Based ◽  
Performance Requirements ◽  
Engine Design

Large bore reciprocating internal combustion engines are used in a wide variety of applications such as power generation, transportation, gas compression, mechanical drives, and mining. Each application has its own unique requirements that influence the engine design & control strategy. The system architecture & control strategy play a key role in meeting the requirements. Traditionally, control design has come in at a later stage of the development process, when the system design is almost frozen. Furthermore, transient performance requirements have not always been considered adequately at early design stages for large engines, thus limiting achievable controller performance. With rapid advances in engine modeling capability, it has now become possible to accurately simulate engine behavior in steady-states and transients. In this paper, we propose an integrated model-based approach to system design & control of reciprocating engines and outline ideas, processes and real-world case studies for the same. Key benefits of this approach include optimized engine performance in terms of efficiency, transient response, emissions, system and cost optimization, tools to evaluate various concepts before engine build thus leading to significant reduction in development time & cost.

Research on Dynamic Authorization Access Control Strategy Model of Distributed Multi-Organization MIS

2012 ◽  
Vol 263-266 ◽  
pp. 1461-1466
Author(s):  
Xiao Ming Meng ◽  
Jian Hua Zhang
Keyword(s):  
Access Control ◽  
Control Strategy ◽  
Control Process ◽  
Shared Resources ◽  
Organization Management ◽  
System A ◽  
Multi Stage ◽  
Strategy Model ◽  
Key Terms ◽  
Dynamic Authorization

Focus on the problem of dynamic authorization access control of Distributed Multi-Organization Management Information System (DMOMIS), the system resources are divided into two kinds: relatively independent resources and shared resources. These two kinds of resources were used different authorization system to authorize. The relatively independent resources were authorized by using distributed authorization system (DA), and the similar and shared resources were authorized by using authorized system (A). According to the key terms definition, the system hypothesis and the idea of dynamic programming, then the dynamic authorization access control process of DMOMIS was abstracted as a multi stage users authorization process based on resources, and put out the dynamic authorization access control strategy model of DMOMIS, at last, depicted its execution process.

Exploring energy-saving refrigerators through online e-commerce reviews: an augmented mining model based on machine learning methods

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yuyan Luo ◽  
Zheng Yang ◽  
Yuan Liang ◽  
Xiaoxu Zhang ◽  
Hong Xiao
Keyword(s):  
Machine Learning ◽  
Energy Saving ◽  
Online Reviews ◽  
Learning Methods ◽  
Content Type ◽  
Machine Learning Methods ◽  
Model Based ◽  
Review Mining ◽  
Strategy Model ◽  
Mining Model

PurposeBased on climate issues and carbon emissions, this study aims to promote low-carbon consumption and compel consumers to actively shift to energy-saving appliances. In this big data era, online reviews in social and electronic commerce (e-commerce) websites contain valuable product information, which can facilitate firm business strategies and consumer comparison shopping. This study is designed to advance existing research on energy-saving refrigerators by incorporating machine learning models in the analysis of online reviews to provide valuable suggestions to e-commerce platform managers and manufacturers to effectively understand the psychological cognition of consumers.Design/methodology/approachThis study proposes an online e-commerce review mining and management strategy model based on “data acquisition and cleaning, data mining and analysis and strategy formation” through multiple machine learning methods, namely, Bayes networks, support vector machine (SVM), latent Dirichlet allocation (LDA) and importance–performance analysis (IPA), to help managers.FindingsBased on a case study of one of the largest e-commerce platforms in China, this study linguistically analyzes 29,216 online reviews of energy-saving refrigerators. Results indicate that the energy-saving refrigerator features that consumers are generally satisfied with are, in sequential order, logistics, function, price, outlook, after-sales service, brand, quality and space. This study also identifies ten topics with 100 keywords by analyzing 18 different refrigerator models. Finally, based on the IPA, this study allocates different priorities to the features and provides suggestions from the perspective of consumers, the government and manufacturers.Research limitations/implicationsIn terms of limitations, future research may focus on the following points. First, the topics identified in this study derive from specific points in time and reviews; thus, the topics may change with the text data. A machine learning-based online review analysis platform could be developed in the future to dynamically improve consumer satisfaction. Moreover, given that consumers' needs may change over time, e-commerce platform types and consumer characteristics, such as user profiles, can be incorporated into the model to effectively analyze trends in consumers' perceived dimensions.Originality/valueThis study fills the gap in previous research in this field, which uses small-sample data for qualitative analysis, while integrating management ideas and proposes an online e-commerce review mining and management strategy model based on machine learning methods. Moreover, this study considers how consumers' emotional and thematic preferences for products affect their purchase decision-making from the perspective of their psychological perception and linguistically analyzes online reviews of energy-saving refrigerators using the proposed mining model. Through the improved IPA model, this study provides optimizing strategies to help e-commerce platform managers and manufacturers.

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