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共 257 条记录，以下是171-180 订阅

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An Agent Based Trading Game for Risk Adversity Level Estimation

An Agent Based Trading Game for Risk Adversity Level Estimat...

引用

international conference of soft computing and pattern recognition (socpar)

作者： Pawan Pandey Sambatur Hemant Doan Van Khanh Nanyang Business School Students Nanyang Technological University Singapore Nanyang Technological University Singapore Singapore SG

Portfolio optimization based on the behavior and risk appetite of the heterogeneous investor community in financial markets has been very difficult to model and predict accurately. In this paper, firstly we attempt to simulate a multi-agent based stock market; where different types of agents are modeled to trade stocks using various strategies. The observations from trading activity of the user are in turn used to assess the risk adversity level (RAL) by using a suitable fuzzy logic model. RAL score from the fuzzy model serves as input to perform portfolio optimization using genetic algorithm. We further analyze and evaluate the optimum portfolio performance for different risk adversity level.

关键词： Portfolios Computational modeling Stock markets Genetic algorithms pattern recognition Electronic mail Predictive models Fuzzy logic Risk analysis Performance analysis

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A Modified Differential Evolution Algorithm and Its Application to Engineering Problems

A Modified Differential Evolution Algorithm and Its Applicat...

引用

international conference of soft computing and pattern recognition (socpar)

作者： Musrrat Ali Millie Pant Ajith Abraham Department of Paper Technology Indian Institute of Technology Roorkee Saharanpur India Scientific Network for Innovation and Research Excellence Machine Intelligence Research Laboratories Auburn WA USA

In the present study a Modified Differential Evolution (MDE) algorithm is proposed. This algorithm is different in three ways from basic DE. For initialization it utilizes opposition-based learning while in basic DE uniform random numbers serve this task. Secondly, in basic DE mutant individual is random while in MDE it is tournament best and finally MDE utilizes only one set of population as against two sets as used in basic DE. The performance of proposed algorithm is investigated and compared with basic differential evolution. The experiments conducted shows that proposed algorithm outperform the basic DE algorithm in all the benchmark problems and real life applications.

关键词： Design optimization Printing Integer linear programming Constraint optimization Testing Containers pattern recognition Computer applications Laboratories Computer industry

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Instrumented Dynamic Platform for Observing Human Postural Sway: A Preliminary Study

Instrumented Dynamic Platform for Observing Human Postural S...

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international conference of soft computing and pattern recognition (socpar)

作者： A. A. Gopalai D. Gouwanda S. M. N. A. Senanayake Y. Z. Chong School of Engineering Monash University Malaysia

This paper presents a novel design of a dynamic instrumented platform for observing the human postural sway. The body sway parameters were recorded using a force platform that was constructed with FSRs, and was fitted snugly on the surface of the dynamic platform. There are two conditions being studied in this paper, subjects are required to try and achieve a `standing quiet' stance, with their feet in a comfortable position, with their eyes open (EO) and followed by an eye close (EC). The position of the center of pressure was then recorded as a function of time. The discussion and experimental findings of the recorded data will be discussed further in the paper. The sample size of the subjects was set to be 8, with the age of the subject specifically set to be between 25 and 27 - with the average age of 25, to avoid any influence that age might have on affecting the subject's postural sway.

关键词： Instruments Humans Design optimization Printing Integer linear programming Constraint optimization Testing Containers pattern recognition Computer applications

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Activity recognition from Accelerometer Data on a Mobile Phone

引用

10th international Work-conference on Artificial Neural Networks (IWANN 2009)

作者： Brezmes, Tomas Gorricho, Juan-Luis Cotrina, Josep France Telecom R and D Spain Departamento de Telemática UPC Spain

ISBN: (纸本)9783642024801

Real-time monitoring of human movements can be easily envisaged as a useful tool for many purposes and future applications. This paper presents the implementation of a real-time classification system for some basic human movements using a conventional mobile phone equipped with an accelerometer. The aim of this study was to check the present capacity of conventional mobile phones to execute in real-time all the necessary pattern recognition algorithms to classify the corresponding human movements. No server processing data is involved in this approach, so the human monitoring is completely decentralized and only an additional software will be required to remotely report the human monitoring. The feasibility of this approach opens a new range of opportunities to develop new applications at a reasonable low-cost.

关键词： pattern recognition human movement's detection accelerometer

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Data Collecting Strategies for the Improvement of Healthcare Service: Analyzing Dispensing Errors in a Hospital Pharmacy

Data Collecting Strategies for the Improvement of Healthcare...

引用

international conference of soft computing and pattern recognition (socpar)

作者： Yoshiko Habuchi Toshitaka Takenouchi Yoichi Motomura Center for Service Research National Institute of Advanced Industrial Science and Technology AIST Tsukuba Japan Department of Pharmacy Services Showa University Hospital Tokyo Japan

In this report, we first describe the importance of both a quality management system and a risk factor monitoring system for healthcare service. This report also discusses a case study that monitored dispensing errors in a hospital pharmacy. The authors used audit records and then interlinked error data with both location and prescription data to investigate the circumstances and potential causes of these errors. The results suggest that the frequency of prescription of certain drugs is a key factor in these types of errors. Understanding the effects of this high volume of prescriptions in the hospital pharmacy could help prevent errors and increase productivity. This report showed that an effective monitoring system could create concrete improvements and enhance utilization of information.

关键词： Medical services Error analysis Hospitals Quality management Monitoring Frequency Health and safety Computer industry Standardization pattern recognition

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Motif Discovery Using Evolutionary Algorithms

Motif Discovery Using Evolutionary Algorithms

引用

international conference of soft computing and pattern recognition (socpar)

作者： Linlin Shao Yuehui Chen Ajith Abraham School of Information Science and Engineering University of Ji''nan Jinan Shandong China Machine Intelligence Research Laboratories Scientific Network of Innovation and Research Excellence Auburn WA USA

The bacterial foraging optimization (BFO) algorithm is a nature and biologically inspired computing method. We propose an alternative solution integrating bacterial foraging optimization algorithm and tabu search (TS) algorithm namely TS-BFO. We modify the original BFO via established a self-control multi-length chemotactic step mechanism, and introduce rao metric. We utilize it to solve motif discovery problem and compare the experimental result with existing famous DE/EDA algorithm which combines global information extracted by estimation of distribution algorithm (EDA) with differential information obtained by Differential evolution (DE) to search promising solutions. The experiments on real data set selected from TRANSFAC and SCPD database have predicted meaningful motif which demonstrated that TS-BFO and DE/EDA are promising approaches for finding motif and enrich the technique of motif discovery.

关键词： Evolutionary computation Sequences Electronic design automation and methodology Microorganisms Information science Biology computing Databases pattern matching pattern recognition Machine intelligence

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Synergistic-ANN Recognizers for Monitoring and Diagnosis of Multivariate Process Shift patterns

Synergistic-ANN Recognizers for Monitoring and Diagnosis of ...

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international conference of soft computing and pattern recognition (socpar)

作者： Ibrahim Masood Adnan Hassan Faculty of mechanical and manufacturing engineering Universiti Tun Hussein Onn Malaysia Batu Pahat Malaysia Faculty of mechanical engineering Universiti Teknologi Malaysia Skudai Malaysia

An intelligent control chart pattern recognition system is essential for efficient monitoring and diagnosis process variation in automated manufacturing environment. Artificial neural networks (ANN) have been applied for automated recognition of control chart patterns since the last 20 years. In early study, the development of control chart patterns recognizers was mainly based on generalized-ANN model. There has been an increasing trend among researchers to move beyond generalized recognizer particularly for addressing complex recognition tasks. However, the existing works mainly focus on univariate process cases. This paper aims to investigate an effective synergistic-ANN model for on-line monitoring and diagnosis multivariate process patterns. The recognition performances of a generalized-ANN and the parallel distributed ANN recognizers for learning dynamic patterns of multivariate process patterns were discussed.

关键词： pattern recognition Monitoring Design optimization Printing Integer linear programming Constraint optimization Testing Containers Computer applications Laboratories

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Object recognition Using Fourier Descriptors and Genetic Algorithm

Object Recognition Using Fourier Descriptors and Genetic Alg...

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international conference of soft computing and pattern recognition (socpar)

作者： M. Sarfraz Mehmood-ul-Hassan M. Iqbal Department of Information Science Kuwait University Safat Kuwait Department of Computer Science COMSATS Abbottabad Pakistan

This work presents study and experimentation for object recognition when isolated objects are under discussion. The circumstances of similarity transformations, presence of noise, and occlusion have been included as the part of the study. For simplicity, instead of objects, outlines of the objects have been used for the whole process of the recognition. Fourier descriptors have been used as features of the objects. From the analysis and results using Fourier descriptors, the following questions arise: What is the optimum number of descriptors to be used? Are these descriptors of equal importance? To answer these questions, the problem of selecting the best descriptors has been formulated as an optimization problem. Genetic algorithm technique has been mapped and used successfully to have an object recognition system using minimal number of Fourier descriptors. The proposed method assigns, for each of these descriptors, a weighting factor that reflects the relative importance of that descriptor.

关键词： Object recognition Genetic algorithms Shape Image recognition pattern recognition Information science Computer science Fourier transforms Computer errors Computer vision

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A Transparent Classification Model Using a Hybrid soft computing Method

A Transparent Classification Model Using a Hybrid Soft Compu...

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3rd Asia international conference on Modelling and Simulation

作者： Ainon, Raja Noor Lahsasna, Adel Teh, Ying Wah Univ Malaya Fac Comp Sci & Informat Technol Kuala Lumpur Malaysia

ISBN: (纸本)9781424441549

Due to the inherent complexity of many real-world problems, classification models have become an important tool for solving pattern recognition tasks in many disciplines such as medicine, finance and management. Accuracy and transparency are two important criteria that should be satisfied by any classification model. In this paper, a transparent and relatively accurate classifier is developed using a hybrid soft computing technique. The initial fuzzy model is first generated using a clustering method and the transparency and accuracy of the model are then simultaneously optimized using a multi-objective evolutionary technique. The proposed model is tested on two real problems;the first one is related to credit scoring problem while the other is on medical diagnosis. All the data sets used in this study are publicly available at UCI repository of machine learning database.

关键词： fuzzy systems transparency genetic algorithms

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Quantum-Inspired Evolution Strategy

Quantum-Inspired Evolution Strategy

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international conference of soft computing and pattern recognition (socpar)

作者： Hamid Izadinia Mohammad Mehdi Ebadzadeh Computer Engineering and Information Technology Department Amirkabir University of Technology슠 Tehran Iran

Evolution strategy is a suitable method for solving numerical optimization problems whose main characteristic is self adaption of the mutation step size. Finding the promising region in the search space is beneficial in optimization problems. However, in the contemporary ES the next generation is produced in a hyper ellipse and the direction to the optimum is not determined correctly. Therefore it is possible that the mutants are produced in unpromising regions which leads to unsatisfactory convergence. To alleviate this deficiency a novel evolution strategy which is inspired by the quantum computing is proposed in this paper. The proposed algorithm which is called quantum-inspired evolution strategy (QES) can improve the convergence speed and the accuracy by modifying the mutation direction. To demonstrate the effectiveness and applicability of the proposed method, several experiments on a set of numerical optimization problems are carried out. The results show that QES is superior to conventional ES in terms of convergence speed, accuracy and robustness.

关键词： Shape Curve fitting Phase detection Image segmentation Iterative algorithms pattern recognition Information science Data mining Computer graphics Shearing

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