SciTePress - Affiliation Profile

Research.Publish.Connect.

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Affiliation

Select a Subject
Refine Ontology Subject

Beijing Technology and Business University, China

Context (please use complete words only)

Field

Sort by

9 Papers

Intelligent Predicting Method of Water Bloom based RBFNN and LSSVM

Topics: Soft Computing; Neural Networks; AI and Creativity; Simulation

Authors: Liu Zaiwen , Wu Qiaowei and Lv Siying

Affiliation: Beijing Technology and Business University, China

Digital Object Identifier: 10.5220/0004334705920597

Proceedings of ICAART 2013, ISBN: 978-989-8565-39-6

Quick Abstract

Water bloom is one phenomena of eutrophication, and water bloom prediction is always a challenge. A short-term intelligent predicting method based on RBF neural network (RBFNN), and medium-term intelligent predicting method based on least squares support vector machine (LSSVM) for water bloom are proposed in this paper. Including research on the monitoring learning algorithms to the center, width and weight of basis function of RBF network, the width of RBF and fitting and generalization abilities of network, and the function and influence, which the number of RBF hidden level nodes brings to the performance of network, as well as error-corrected algorithm based on gradient descent are analyzed. Least squares support machine, which has long prediction period and high degree of prediction accuracy, needs a small amount of sample can be used to predict the medium-term change discipline of Chl-a (Chlorophyll-a) well. The results of simulation and application show that: RBF neural network can be used to forecast the change of Chl-a in short term well, and LSSVM improves the algorithm of support vector machine (SVM), and it has long-term prediction period, strong generalization ability and high prediction accuracy; and this model provides an efficient new way for medium-term water bloom prediction.

A COLLABORATIVE OPTIMIZATION MODEL FOR STRATEGIC PERFORMANCE

Authors: Zhang Hao , Cui Li , Zhou Yong-sheng and He Ming-ke

Affiliation: Beijing Technology and Business University, China

Digital Object Identifier: 10.5220/0003573306450649

Proceedings of MMLM 2011/ICEIS, ISBN: 978-989-8425-56-0

Quick Abstract

The logical framework formed by enterprise strategic performance which designed from the dimensions of structure, capability and the culture is what we used to refine the key points of strategic performance. To construct a collaborative optimization model for strategic performance, it should be based on the overall optimization framework of collaborative optimization technology with the chaotic optimization method. The objective of system-level optimization is strategic performance optimization. The optimization goal of the subsystem-level is to make the difference between the designed subsystems and the subsystems provided by system-level optimization as little as possible. The numerical simulations show that the model is scientific and feasible.

A COMPREHENSIVE EVALUATION MODEL AND INTELLIGENT PREDICTION METHOD OF WATER BLOOM

Topics: Industrial, Financial and Medical Applications; Computational Neuroscience; Higher Level Artificial Neural Network Based Intelligent Systems; Neural Network Software and Applications; Support Vector Machines

Authors: Zaiwen Liu , Xiaoyi Wang and Wei Wei

Affiliation: College of Computer and Information Engineering and Beijing Technology and Business University, China

Digital Object Identifier: 10.5220/0003682703910394

Proceedings of NCTA 2011/IJCCI, ISBN: 978-989-8425-84-3

Quick Abstract

An integrated evaluative function and intelligent prediction model for water bloom in lakes based on least squares support vector machine( LSSVM) is proposed in this paper, in which main influence factor of outbreak of water bloom is analyzed by rough set theory. First the study of the function involves three aspects: algal average activation energy of photosynthesis, integrated nutritional status index, and transparency, which are considered from the microcosmic level., the macroscopic level and the intuitionistic level respectively. The values of the function are classified properly. At the meantime, the weight value of each evaluative parameter is determined objectively, via the theory of multiple criteria decision making,. By analyzing and calculating the experimental data, the obtained values of the function and the classification results can be verified using the data of the samples. Good agreement is obtained between the results and the fact. The results of simulation and application show that: LSSVM improves the algorithm of support vector machine (SVM).; it has long-term prediction period, strong generalization ability， high prediction accuracy; and needs a small amount of sample and this model provides an efficient new way for medium-term water bloom prediction.

Related Ontology Subjects/Areas/Topics (26)

Artificial Intelligence	Fuzzy Systems	Neurotechnology, Electronics and Informatics
Artificial Intelligence and Decision Support Systems	Health Engineering and Technology Applications	Pattern Recognition
Biomedical Engineering	Higher Level Artificial Neural Network Based Intelligent Systems	Physiological Computing Systems
Biomedical Signal Processing	Human-Computer Interaction	Sensor Networks
Computational Intelligence	Industrial, Financial and Medical Applications	Signal Processing
Computational Neuroscience	Methodologies and Methods	Soft Computing
Computer-Supported Education	Neural Network Software and Applications	Support Vector Machines and Applications
Domain Applications and Case Studies	Neural Networks	Theory and Methods
Enterprise Information Systems	Neurocomputing

AN EMPIRICAL ANALYSIS OF THE RELATIONSHIP BETWEEN SOCIAL CONSUMPTION DEMAND FACTORS AND THE CULTURAL INDUSTRY IN CHINA

Authors: Li Cui , Haoxiong Yang and Hao Zhang

Affiliation: School of Business and Beijing Technology and Business University, China

Digital Object Identifier: 10.5220/0003597406060610

Proceedings of PMSS 2011/ICEIS, ISBN: 978-989-8425-56-0

Quick Abstract

The relationship between social consumption demand factors and the development of Chinese culture industry is analyzed based on the theory of industrial structure. The result indicates that average disposable income of urban residents and Engel coefficient of rural households are related to culture industry very significantly and that the contribution of culture industry to GDP needs to be improved. Three countermeasures are proposed to promote the development of culture industry from two angles, including improving average disposable income of urban residents to increase their consumption ability, reducing Engel coefficient of rural households to improve the quality of life and promoting the construction of public cultural service system.

INVENTORY MANAGEMENT POLICIES OF GOLD JEWELRY RETAILERS

Authors: Jingmin Zhang , Yongsheng Zhou , Zhe Zhou and Huanjun Yang

Affiliation: Beijing Technology and Business University, China

Digital Object Identifier: 10.5220/0003589005170522

Proceedings of DMLSC 2011/ICEIS, ISBN: 978-989-8425-55-3

Quick Abstract

With the gradually increasing pressure of market competition and the diversification of consumers’ choices, more and more gold jewelry retailers begin to seek the ways and means to reduce costs and improve profits, inventory management also is given more meaning and significance. Starting from the logistics characteristics of the gold jewelry, This article analyzes the prevalent inventory problems of gold jewelry retailers, such as low inventory turns, inventory structural imbalance and so on, and main reasons these problems emerge. On this basis, from supplier management, customer demand forecasting, replenishment strategy and the goods on display and other aspects respectively, putting forward the inventory management strategy of gold jewelry retailers.

NEURAL NETWORK-BASED PROCUREMENT MODE SELECTION OF MRO MATERIALS

Authors: Zhen Huang , Yiran Zhang , Haoxiong Yang , Yongsheng Zhou and Li Cui

Affiliation: Beijing Technology and Business University, China

Digital Object Identifier: 10.5220/0003589205230526

Proceedings of DMLSC 2011/ICEIS, ISBN: 978-989-8425-55-3

Quick Abstract

Maintenance, Repair and operations (MRO) have following features: large sum of types, relatively low requirement, and high transition cost. It costs companies a lot of money and human resource on MRO procurement. In order to make MRO procurement more efficient and scientific, this paper compared the cost of two MRO supply chain modes to get a scope for each mode. And then SOM neural networks method can be used to cluster the materials. Different types of materials take advantage of different procurement mode.

THE IMPACT OF THE CONCENTRATION RATE OF THE INTERNATIONAL CONTAINER LINER MARKET ON CHINESE CONTAINER FREIGHT INDEX

Authors: Cui Li , Zhou Yong Sheng and He Mingke

Affiliation: Beijing Technology and Business University, China

Digital Object Identifier: 10.5220/0003597906110616

Proceedings of PMSS 2011/ICEIS, ISBN: 978-989-8425-56-0

Quick Abstract

At the beginning of the 21st century, a wave of company merging was stirred up in the global container liner market. The relationship between market concentration and China container freight index (CCFI) was analyzed through economic theory from the year 2000 to 2005 when container liner freighting industry reached the high point of the merging wave. It was found that the increasing market share of the top 20 shippers did not affect CCFI to some extent. But the high degree of monopoly had impaired the fairness of shipping market and also affected the free competition of Chinese shipping market. Some policy suggestions were given to deal with the potential mergers.

URBAN MOTOR VEHICLE LIMITING POLICY BASED ON SYSTEM DYNAMICS

Authors: Haoxiong Yang , Zhao Zhao , Yongsheng Zhou and Hao Zhang

Affiliation: Beijing Technology and Business University, China

Digital Object Identifier: 10.5220/0003584205390542

Proceedings of PMSS 2011/ICEIS, ISBN: 978-989-8425-56-0

Quick Abstract

The governance of urban traffic jam is a hot topic in the process of urban development in China. From the perspective of system dynamics, this paper point out that the urban motor vehicle limiting policy used to control traffic jam needs a strong public transport system, and if there is no convenient public transport system, the limiting policy only has short-term effect. This paper also put forward some relevant countermeasures at last.

VEHICLE ROUTING PROBLEM WITH MULTI-DEPOT AND MULTI-TASK

Authors: Haoxiong Yang ¹ , Li Jing ¹ , Yongsheng Zhou ² and Mingke He ²

Affiliations: ¹ School of Business and Beijing Technology and Business University, China , ² Beijing Technology and Business University, China

Digital Object Identifier: 10.5220/0003573406500655

Proceedings of MMLM 2011/ICEIS, ISBN: 978-989-8425-56-0

Quick Abstract

This paper presents a new mathematical model of the vehicle routing problem in the context of city distribution, which considers multi-depot, multi-model vehicles and multi-task. The objective function includes three parts: transport cost, deadheading cost and time cost. To solve this mathematical model, a self-adaptive and polymorphic ant colony algorithm (APACA) has been introduced. Finally, a case study is presented to compare the results based on APACA with that under stochastic condition. Simulation results show that APACA is an effective and desirable algorithm for solving the mathematical model.