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Quantum-Inspired Evolution Strategy

Quantum-Inspired Evolution Strategy

引用

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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Experimental Use of Electronic Nose for Analysis of Volatile Organic Compound (VOC)

Experimental Use of Electronic Nose for Analysis of Volatile...

引用

international conference on Multimedia, Signal Processing and Communication Technologies

作者： Saeed, Syed Hasan Abbas, Zia Gopal, Bal Integral Univ Dept Elect & Comm Engg Lucknow Uttar Pradesh India

ISBN: (纸本)9781424436033

An electronic nose is an instrument intended to mimic the human sense of smell. Electronic noses (e-nose) employ an array of chemical gas sensors, a sample handling system and a pattern recognition system. pattern recognition provides a higher degree of selectivity and reversibility to the system leading to an extensive range of applications. These ranges from the food and medical industries to environmental monitoring and process control. Many other types of different gas sensors available. These include conducting polymers (CP), metal oxide semiconductors (MOS), piezoelectric, optical fluorescence, quartz crystal microbalance (QCM) and Amperometric gas sensors. The ideal gas sensor would exhibit reliability, robustness, sensitivity, selectivity and reversibility. High selectivity with high reversibility is difficult to attain. After signal processing and feature extraction the output of the sensors provide a unique "smellprint" for that substances which can he used to classify, measure concentration, or verify quality. The present paper illustrates the function of electronic nose, its application and investigates the effective use of e-nose in detecting gases that have some smell developed by the volatile organic compounds (VOC) like ethanol, acetone and benzene at different concentrations. The response and characteristics prove that the Electronic nose is a reliable instrument which can be used for environment control (air quality, pollutants, and gas emission levels), medical science (urine, skin and breath odour etc.), food industry (coffee, milk, soft drink fish, meat etc.), pharmaceutics, chemical industry, Defence and security industries (detecting humanitarian land mines etc.) and semiconductor industrial processes.

关键词： Electronic noses chemical sensors sensor array pattern recognition volatile organic compound smell print

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The Application of the Locally Linear Model Tree on Customer Churn Prediction

The Application of the Locally Linear Model Tree on Customer...

引用

international conference of soft computing and pattern recognition (SOCPAR)

作者： Amineh Ghorbani Fattaneh Taghiyareh Caro Lucas Faculty of Technology Policy and Management Delft University of Technnology Delft Netherlands Department of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Tehran Iran

Acquiring new customers in any business is much more expensive than trying to keep the existing ones. Thus many prediction models are presented to detect churning customers. The objective of this paper was to improve the predictive accuracy and interpretability of churn detection. For this purpose, the application of the locally linear model tree (LOLIMOT) algorithm, which integrates the advantage of neural networks, tree model and fuzzy modeling, was experimented. Applied to the data of a major telecommunication company, the method is found to improve prediction accuracy significantly compared to other algorithms, such as artificial neural networks, decision trees, and logistic regression. The results also indicate that LOLIMOT can have accurate outcome in extremely unbalanced datasets.

关键词： Predictive models Decision trees Neural networks Accuracy Artificial neural networks Logistics Regression tree analysis pattern recognition Application software conference management

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CBGP: Classification Based on Gradual patterns

CBGP: Classification Based on Gradual Patterns

引用

international conference of soft computing and pattern recognition (SOCPAR)

作者： Yeow Wei Choong Lisa Di Jorio Anne Laurent Dominique Laurent Maguelonne Teisseire Dept. of IT HELP University College Kuala Lumpur Malaysia Universite de Montpellier Montpellier Languedoc-Roussillon FR LIRMM University of Montpellier II CNRS Montpellier France LIRMM CNRS Montpellier France ETIS University of Cergy-Pontoise CNRS Cergy-Pontoise France ETIS CNRS Cergy Pontoise France UMR Tetis CEMA GREF Montpellier France CEMAGREF UMR Tetis Montpellier France

In this paper, we address the issue of mining gradual classification rules. In general, gradual patterns refer to regularities such as "The older a person, the higher his salary''. Such patterns are extensively and successfully used in command-based systems, especially in fuzzy command applications. However, in such applications, gradual patterns are supposed to be known and/or provided by an expert, which is not always realistic in practice. In this work, we aim at mining from a given training dataset such gradual patterns for the generation of gradual classification rules. Gradual classification rules thus refer to rules where the antecedent is a gradual pattern and the conclusion is a class value.

关键词： Neoplasms Classification tree analysis Cancer Gene expression Decision trees pattern recognition Educational institutions Remuneration Fuzzy systems Data mining

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IMPLEMENTATION OF WEB CRAWLER

IMPLEMENTATION OF WEB CRAWLER

引用

2nd international conference on Emerging Trends in Engineering and Technology (ICETET09)

作者： Gupta, Pooja Johari, Kalpana Linagay's University India Center for Development of Advanced Computing NOIDA India

ISBN: (纸本)9781424452507

The World Wide Web is an interlinked collection of billions of documents formatted using HTML. Ironically the very size of this collection has become an obstacle for information retrieval. The user has to shift through scores of pages to come upon the information he/she desires. Web crawlers are the heart of search engines. Web crawlers continuously keep on crawling the web and find any new web pages that have been added to the web, pages that have been removed from the web. Due to growing and dynamic nature of the web;it has become a challenge to traverse all URLs in the web documents and to handle these URLs. A focused crawler is an agent that targets a particular topic and visits and gathers only relevant web pages. In this dissertation I had worked on design and working of web crawler that can be used for copyright infringement. We will take one seed URL as input and search with a keyword, the searching result is based on keyword and it will fetch the web pages where it will find that keyword. This focused based crawler approach retrieve documents that contain particular keyword from the user's query;we are implementing this using breadth-first search. Now, when we retrieved the web pages we will apply pattern recognition over text. We will give one file as input and apply the pattern recognition algorithms. Here, pattern symbolizes text only and check how much text is available on the web page. The algorithms that I had used for pattern search are Knutt-Morri-Pratt, Boyer-Moore, Finite Automata algorithm.

关键词： Search engine focus crawler pattern recognition copyright infringement

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PSO-Based Optimization of State Feedback Tracking Controller for a Flexible Link Manipulator

PSO-Based Optimization of State Feedback Tracking Controller...

引用

international conference of soft computing and pattern recognition (SOCPAR)

作者： Mahmud Iwan Solihin Wahyudi Rini Akmeliawati Intelligent Mechatronics System Research Group International Islamic University Malaysia Kuala Lumpur Malaysia

In this paper, state feedback control design for tracking control of a flexible link manipulator is considered. The computation of state feedback control gains is conventionally handled by pole placement method or LQR method via Riccati equation. Unfortunately, they still possess trial-and-error approach in choosing their parameters. Particularly, choosing elements of Q and R matrices in the state feedback control design using LQR method has to be done by trial. Therefore, an intelligent method to resolve this problem is proposed by adopting PSO-based optimization. Experimental work is carried out to evaluate effectiveness of the proposed method.

关键词： State feedback Control systems Riccati equations Feedback control Linear feedback control systems Optimization methods Mechatronics Control design Manipulator dynamics Vibration control

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An Improved Discrete Particle Swarm Optimization in Evacuation Planning

An Improved Discrete Particle Swarm Optimization in Evacuati...

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international conference of soft computing and pattern recognition (SOCPAR)

作者： Marina Yusoff Junaidah Ariffin Azlinah Mohamed Faculty of Information Technology & Quantitative Sciences Universiti Teknologi MARA Shah Alam Selangor Darul Ehsan Malaysia Institute for Infrastructure Engineering & Sustainable Management Faculty of Civil Engineering Universiti Teknologi MARA Shah Alam Selangor Darul Ehsan Malaysia

In any flash flood evacuation operation, vehicle assignment at the inundated areas is vital to help eliminate loss of life. Vehicles of various types and capacities are used to evacuate victims to relief centers. This paper examines combinatorial optimization approach with the objective function to assign a specified number of vehicles with maximum number of evacuees to the potential inundated areas. Discrete particle swarm optimization (DPSO) and improved DPSO are proposed and experimented on. Results are presented and compared. Improved DPSO with the proposed min-max approach yields better performance for all four testing categories. Experimenting on a large number of evacuees could further improve the performance of the DPSO.

关键词： Particle swarm optimization Vehicles Floods Information technology pattern recognition Technology planning Automotive engineering conference management Technology management Engineering management

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Type-2 Fuzzy Sets Applied to pattern Matching for the Classification of Cries of Infants under Neurological Risk

Type-2 Fuzzy Sets Applied to Pattern Matching for the Classi...

引用

5th international conference on Intelligent computing

作者： Santiago-Sanchez, Karen Reyes-Garcia, Carlos A. Gomez-Gil, Pilar Natl Inst Astrophys Opt & Elect Dept Comp Sci Mexico City 72840 DF Mexico

ISBN: (纸本)9783642040696

Crying is an acoustic event that contains information about the functioning of the central nervous system, and the analysis of the infant's crying can be a support in the distinguishing diagnosis in cases like asphyxia and hyperbilirrubinemia. The classification of baby cry has been intended by the use of different types of neural networks and other recognition approaches. In this work we present a pattern classification algorithm based on fuzzy logic Type 2 with which the classification of infant cry is realized. Experiments as well as results are also shown.

关键词： Fuzzy Sets pattern Matching Neurological Risk

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SEMG De-noising based on the Lifting Wavelet Transform

SEMG De-noising based on the Lifting Wavelet Transform

引用

3rd international conference on Bioinformatics and Biomedical Engineering

作者： Luo Zhi-zeng Li Ya-fei Meng Ming Hangzhou Dianzi Univ Robot Res Inst Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781424429011

In order to improve the surface electromyography (SEMG) pattern recognition ability of hand movement, this paper presents a de-noising method based on lifting wavelet transform. Firstly, high frequency detail coefficients of multilayer signals are obtained from original SEMG using the lifting wavelet decomposition with lifting algorithm. Then the coefficients are treated by the soft and the hard threshold method separately. Finally, a noise decreased signal is obtained through reconstructing the filtered coefficients. The de-noising experiments of standard sine adding noise signal and real SEMG are carried on. The results show that the lifting wavelet is an obvious better de-noising method compared to the first generation wavelet. In addition, the hard threshold method is more ideal for SEMG de-noising than the soft threshold method.

关键词： Surface electromyography(SEMG) Lifting algorithm soft threshold Hard threshold

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Restricted growth string for video-type classification

Restricted growth string for video-type classification

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2nd international Workshop on Advanced Computational Intelligence, IWACI 2009

作者： Orellana, Pedro Luis Sánchez Jiménez, José Torres Sánchez, Claudio Castellanos Laboratory of Information Technology Centre for Research and Advanced Studies LIT Cinvestav TamaulipasCiudad-Victoria Tamaulipas Mexico

ISBN: (纸本)9783642031557

The use of videos to extract information from the environment is one of the most challenging task in the computer vision area. The video sequences are of particular relevance for the recognition of humans in environments;in spite of the large databases existing in the literature, there is a lack of the uniformity among them which causes difficulties at the moment of making comparisons. The main reason is the restrictions on the conditions of the sequences (like illumination). To solve this problem we are proposing a set of 5 characteristics that highly influence the human's gait recognition, also we propose the use of the Restricted Grow Strings to cluster the data bases of characteristics that represent the conditions in the videos. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： pattern recognition

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