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Intelligent value-based customer segmentation method for campaign management: A case study of automobile retailer

EXPERT SYSTEMS WITH APPLICATIONS 2008年第4期34卷 2754-2762页

作者： Chan, Chu Chai Henry Chaoyang Univ Technol Dept Ind Engn & Management E Business Res Lab Wufong Township Taichung County Taiwan

Most marketers have difficulty in identifying the right customers to engage in successful campaigns. So far, customer segmentation is a popular method that is used for selecting appropriate customers for a launch campaign. Unfortunately, the link between customer segmentation and marketing campaign is missing. Another problem is that database marketers generally use different models to conduct customer segmentation and customer targeting. This study presents a novel approach that combines customer targeting and customer segmentation for campaign strategies. This investigation identifies customer behavior using a recency, frequency and monetary (RFM) model and then uses a customer life time value (LTV) model to evaluate proposed segmented customers. Additionally, this work proposes using generic algorithm (GA) to select more appropriate customers for each campaign strategy. To demonstrate the efficiency of the proposed method, this work performs an empirical study of a Nissan automobile retailer to segment over 4000 customers. The experimental results demonstrate that the proposed method can more effectively target valuable customers than random selection. (c) 2007 Published by Elsevier Ltd.

关键词： customer segmentation generic algorithm customer lifetime value campaign management

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Differential Evolutionary Bayesian Classifier

Differential Evolutionary Bayesian Classifier

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IEEE International Conference on Granular Computing

作者： Deng, Wanyu Zheng, Qinghua Wang, Yulan Chen, Lin Xu, Xuebin Xi An Jiao Tong Univ MOE KLINNS Lab Xian 710049 Peoples R China Xi An Jiao Tong Univ SKLMS Lab Xian 710049 Peoples R China Xi An Jiao Tong Univ Dept Comp Sci & Technol Xian Peoples R China Inst Post & Telecommun Xian Dept Comp Sci & Technol Xian Peoples R China Xi An Jiao Tong Univ Sch Foreign Language Xian Peoples R China

ISBN: (纸本)9781424425129

Naive Bayes (NB) based on the attribute independence assumption has been widely applied in many domains for its simplicity and efficiency. However, the independence assumption is often violated in many real-world applications. In response to this problem, a mount of research has been carried out to improve NBs accuracy by mitigating the attribute independence assumption, for example Lazy learning of Bayesian Rules(LBR), Tree Augmented Naive Bayes (TAN) and Averaged One-Dependence Estimator(AODE). AODE which averages all Super Parent One-dependence Estimators (SPODE) has attracted widely attention for its outstanding performance. Because of the different role of every SPODEs, the performance will be expected to be improved significantly if different weights are assigned to these SPODEs. We proposed the framework of linear weighted SPODE ensemble and efficient learning strategy of weights based on differential evolution. The experience has shown that the proposed algorithm can generate better performance in most case than NB, A ODE, WAODE, TAN and LBR.

关键词： Differential Evolutionary generic algorithm Naive Bayes Classifier AODE

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Searching for optimal conditions of combined pumping of erbium-doped fiber amplifiers by means of genetic algorithm

Searching for optimal conditions of combined pumping of erbi...

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International Conference on Lasers, Applications, and Technologies

作者： Varaksa, Yury A. Khodasevich, Mikhail A. Natl Acad Sci Belarus Inst Phys Minsk BELARUS

The modeling of erbium-doped fiber amplifier with three-level forward pumping and quasi-two-level backward pumping has been performed. The optimal pumping conditions for achievement of the flattest gain spectrum have ... 详细信息

ISBN: (纸本)9780819468895

关键词： erbium-doped fiber amplifier (EDFA) combined pumping bidirectional pumping generic algorithm

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Discrete Transition System Model and Verification for Mitochondrially Mediated Apoptotic Signaling Pathways

Discrete Transition System Model and Verification for Mitoch...

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作者： Lam, Huy Hong Virginia Tech | University

Computational biology and bioinformatics for apoptosis have been gaining much momentum due to the advances in computational sciences. Both fields use extensive computational techniques and modeling to mimic real world behaviors. One problem of particular interest is on the study of reachability, in which the goal is to determine if a target state or protein concentration in the model is realizable for a signaling pathway. Another interesting problem is to examine faulty pathways and how a fault can make a previously unrealizable state possible, or vice versa. Such analysis can be extremely valuable to the understanding of apoptosis. However, these analyses can be costly or even impractical for some approaches, since they must simulate every aspect of the model. Our approach introduces an abstracted model to represent a portion of the apoptosis signaling pathways as a finite state machine. This abstraction allows us to apply hardware testing and verification techniques and also study the behaviors of the system without full simulation. We proposed a framework that is tailor-built to implement these verification techniques for the discrete model. Through solving Boolean constraint satisfaction problems (SAT-based) and with guided stimulation (Genetic algorithm), we can further extract the properties and behaviors of the system. Furthermore, our model allows us to conduct cause-effect analysis of the apoptosis signaling pathways. By constructing single- and double-fault models, we are able to study what fault(s) can cause the model to malfunction and the reasons behind it. Unlike simulation, our abstraction approach allows us to study the system properties and system manipulations from a different perspective without fully relying on simulation. Using these observations as hypotheses, we aim to conduct laboratory experiments and further refine our model.

关键词： SAT Mitochondria Model Checking Reachability Analysis generic algorithm Apoptosis Fault Analysis Thesis

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AN EXTENDED CONTRACT-NET NEGOTIATION MODEL BASED ON TASK COALITION AND GENETIC algorithm

AN EXTENDED CONTRACT-NET NEGOTIATION MODEL BASED ON TASK COA...

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2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

作者： HAI-JUN TAO YA-DONG WANG MAO-ZU GUO School of Computer Science & Technology Harbin Institute of Technology Harbin 150001 China

Multi-agent negotiation has been one of the key problems in the multi-agent research *** extended contract-net negotiation model based on task coalition and genetic algorithm is presented after analyzing the advantage and disadvantage of the classical contract-net negotiation *** definition method and coalition generation algorithm are given.A specialized genetic algorithm, which is optimized by optimized initial colony selection, optimized parent crossover/mutation and the using of Metropolis rule, is used to solve the task allocation in the *** algorithm improves the efficiency of task allocation and reduces the communication cost By testing and analyzing an example of a missile defense system, it is proved that the model can reduce the negotiation cost effectively contrast with the classical contract-net model on the basis of ensuring the negotiation quality.

关键词： Multi-agent system Negotiation Task coalition generic algorithm Task allocation

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Evolutionary design in a multi-agent design environment

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APPLIED SOFT COMPUTING 2006年第2期6卷 207-220页

作者： Liu, H Tang, MX Shandong Normal Univ Sch Informat & Management Jinan Peoples R China Hong Kong Polytech Univ Sch Design Design Technol Res Ctr Hong Kong Hong Kong Peoples R China

This paper presents a novel evolutionary design approach in a multi-agent design environment. Multi-agent system architecture offers a promising framework for dynamically managing cooperative agents in a distributed environment while the tree structure based generic algorithm provides a foundation for supporting evolutionary and innovative design abilities. Design is a complex knowledge discovery process. Creative design is a human trait that is not easily converted into a computational tool. Rather than to implement the innovative design by computers, this environment is used to stimulate the imagination of designers and extend their thinking space. It wants to explore a feasible and useful evolutionary approach in a distributed environment that will give the designers concrete help for the creative designs. This approach is illustrated by a mobile phone design example, which used binary algebraic expression tree to form sketch shapes and a feature based product tree to produce component combination choices. Because evolution is guided by human selectors, the evolutionary algorithm is not complex. It shows that approach is able to generate some creative solutions, demonstrating the power of explorative evolution. (C) 2005 Elsevier B. V. All rights reserved.

关键词： multi-agent system evolutionary computing generic algorithm computer-aided design creative design

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FAULT DIAGNOSIS OF ROTATING MACHINERY USING KNOWLEDGE-BASED FUZZY NEURAL NETWORK

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Applied Mathematics and Mechanics(English Edition) 2006年第1期27卷 99-108页

作者：李如强陈进伍星 The State Key Laboratory of Vibration

A novel knowledge-based fuzzy neural network （KBFNN） for fault diagnosis is presented. Crude rules were extracted and the corresponding dependent factors and antecedent coverage factors were calculated firstly from the diagnostic sample based on rough sets theory. Then the number of rules was used to construct partially the structure of a fuzzy neural network and those factors were implemented as initial weights, with fuzzy output parameters being optimized by genetic algorithm. Such fuzzy neural network was called KBFNN. This KBFNN was utilized to identify typical faults of rotating machinery. Diagnostic results show that it has those merits of shorter training time and higher right diagnostic level compared to general fuzzy neural networks.

关键词： rotating machinery fault diagnosis rough sets theory fuzzy sets theory generic algorithm knowledge-based fuzzy neural network

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CHOOSE STRATEGIC ACTION BASED ON TWO-STAGE GAME

CHOOSE STRATEGIC ACTION BASED ON TWO-STAGE GAME

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第十二届工业工程和工程管理国际会议

作者： YE Chun ,XIK Kefan,CHEN Yalin Postdoctoral Programs in Management Science & Engineering, Wuhan university of technology, Hubei,PR. China,430077 School of management science, Wuhan university of technology ,Hubei, PR. China ,430077 Institution of system engeering, Wuhan University, Hubei, PR. China,430072

The research on choosing strategic action is still in the qualitative domain. From this point,the paper firstly builds the model of strategic choice based on two-stage game. Secondly, it denotes the game as quadratic bi-level programming problem and presents the corresponding algorithm solving it to find out the equilibrium consequence of the game. Finally,apply it to the enterprise to help it make sure the scale of Research & Development Investment by the model and algorithm. The feedback from the enterprise proves the effective,efficient of them

关键词： two-stage game strategic action the quadratic bi-level programming problem generic algorithm

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Minimizing staircase errors in the orthogonal layered manufacturing system

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2005年第3期2卷 276-284页

作者： Yang, Y Fuh, JYH Loh, HT Wong, YS Natl Univ Singapore Dept Mech Engn Singapore 117576 Singapore

The factors that generally affect the slicing error in layered manufacturing (LM) processes are first analyzed, and issues pertaining to the current methods to deal with the slicing error are discussed in this paper. A method based on a recently developed and implemented orthogonal LM system to reduce the overall slicing error is presented. In this method, the flat region is separated from the stereolithography (STL) model and different processing methods are applied to the different areas in the part geometry. In addition, the mathematical model for calculating the slicing error is derived and an approach based on a genetic algorithm has been developed to optimize the build orientation in terms of minimizing the slicing error. Case studies are given to demonstrate the effectiveness and efficiency of the method.

关键词： build orientation generic algorithm orthogonal layered manufacturing (LM) process planning volume decomposition

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Global optimization of a feature-based process sequence using GA and ANN techniques

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2005年第15期43卷 3247-3272页

作者： Ding, L Yue, Y Ahmet, K Jackson, M Parkin, R Univ Luton Fac Creat Arts Technol & Sci Luton LU1 3JU Beds England Univ Loughborough Mechatron Ctr Wolfson Sch Management & Mfg Engn Loughborough LE11 3TU Leics England

Operation sequencing has been a key area of research and development for computer-aided process planning (CAPP). An optimal process sequence could largely increase the efficiency and decrease the cost of production. Genetic algorithms (GAs) are a technique for seeking to `breed' good solutions to complex problems by survival of the fittest. Some attempts using GAs have been made on operation sequencing optimization, but few systems have intended to provide a globally optimized fittest function definition. In addition, most of the systems have a lack of adaptability or have an inability to learn. This paper presents an optimization strategy for process sequencing based on multi-objective fittness:minimum manufacturing cost, shortest manufacturing time and best satisfaction of manufacturing sequence rules. A hybrid approach is proposed to incorporate a genetic algorithm, neural network and analytical hierarchical process (AHP) for process sequencing. After a brief study of the current research, relevant issues of process planning are described. A globally optimized fittness function is then defined including the evaluation of manufacturing rules using AHP, calculation of cost and time and determination of relative weights using neural network techniques. The proposed GA-based process sequencing, the implementation and test results are discussed. Finally, conclusions and future work are summarized.

关键词： process sequencing features generic algorithm neural network optimization

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