Search results for: Hybrid Evolutionary Algorithm

Authors: G.Mehdiyeva, M.Imanova, V.Ibrahimov

Abstract:

Taking into account that many problems of natural sciences and engineering are reduced to solving initial-value problem for ordinary differential equations, beginning from Newton, the scientists investigate approximate solution of ordinary differential equations. There are papers of different authors devoted to the solution of initial value problem for ODE. The Euler-s known method that was developed under the guidance of the famous scientists Adams, Runge and Kutta is the most popular one among these methods. Recently the scientists began to construct the methods preserving some properties of Adams and Runge-Kutta methods and called them hybrid methods. The constructions of such methods are investigated from the middle of the XX century. Here we investigate one generalization of multistep and hybrid methods and on their base we construct specific methods of accuracy order p = 5 and p = 6 for k = 1 ( k is the order of the difference method).

Keywords: Multistep and hybrid methods, initial value problem, degree and stability of hybrid methods

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Authors: Nur Suraya Anis Ahmad Bakhtiar, Hazizan Md Akil

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In the present work, the dielectric properties of Epoxy/MWCNT-muscovite HYBRID and MIXED composites based on a ratio 30:70 were studied. The multi-wall carbon nanotubes (MWCNT) were prepared using two methods: (a) MWCNTmuscovite hybrids were synthesised by chemical vapour deposition (CVD) and (b) physically mixing muscovite with MWCNT. The effects of different preparation of the composites and filler loading were evaluated. It was revealed that the dielectric constants of HYBRID epoxy composites are slightly higher than MIXED epoxy composites. It was also indicated that the dielectric constant increased by increasing the MWCNT filler loading.

Keywords: MWCNT-Muscovite, Epoxy, Dielectric Properties, Hybrid Composite.

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Authors: Parviz Fattahi

Abstract:

Scheduling for the flexible job shop is very important in both fields of production management and combinatorial optimization. However, it quit difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. The combining of several optimization criteria induces additional complexity and new problems. In this paper, a Pareto approach to solve the multi objective flexible job shop scheduling problems is proposed. The objectives considered are to minimize the overall completion time (makespan) and total weighted tardiness (TWT). An effective simulated annealing algorithm based on the proposed approach is presented to solve multi objective flexible job shop scheduling problem. An external memory of non-dominated solutions is considered to save and update the non-dominated solutions during the solution process. Numerical examples are used to evaluate and study the performance of the proposed algorithm. The proposed algorithm can be applied easily in real factory conditions and for large size problems. It should thus be useful to both practitioners and researchers.

Keywords: Flexible job shop, Scheduling, Hierarchical approach, simulated annealing, tabu search, multi objective.

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Authors: Luciano Nieddu, Giuseppe Manfredi

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In this paper a Pattern Recognition algorithm based on a constrained version of the k-means clustering algorithm will be presented. The proposed algorithm is a non parametric supervised statistical pattern recognition algorithm, i.e. it works under very mild assumptions on the dataset. The performance of the algorithm will be tested, togheter with a feature extraction technique that captures the information on the closed two-dimensional contour of an image, on images of industrial mineral ores.

Keywords: K-means, Industrial ores classification, Invariant Features, Supervised Classification.

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Authors: Jung D. Kwon, Seong J. Kim, Sana U. Nasir, Sung K. Ha

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An advanced composite flywheel rotor consisting of intra and inter hybrid rims was designed to optimally increase the energy capacity, and was manufactured using filament winding with in-situ curing. The flywheel has recently attracted considerable attention from many investigators since it possesses great potential in many energy storage applications, including electric utilities, hybrid or electric automobiles, and space vehicles. In this investigation, a comprehensive study was conducted with the intent to implement composites in high performance flywheel applications.The inner two intra-hybrid rims (rims 1 and 2) were manufactured as a whole part through continuous filament winding under in-situ curing conditions, and so were the outer two rims (rims 3 and 4). The outer surface of rim 2 and the inner surface of rim 3 were CNC-tapered for press-fitting. Machined rims were finally press-fitted using a hydraulic press with a maximum compressive force of approximately 1000 ton.

Keywords: composite flywheel rotor, inter hybrid, intra hybrid, multi-rim, interference, in-situ cure, press-fit

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Authors: Changqing Yang, Jianhua Hou, Beibo Qin

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A numerical method for Riccati equation is presented in this work. The method is based on the replacement of unknown functions through a truncated series of hybrid of block-pulse functions and Chebyshev polynomials. The operational matrices of derivative and product of hybrid functions are presented. These matrices together with the tau method are then utilized to transform the differential equation into a system of algebraic equations. Corresponding numerical examples are presented to demonstrate the accuracy of the proposed method.

Keywords: Hybrid functions, Riccati differential equation, Blockpulse, Chebyshev polynomials, Tau method, operational matrix.

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Authors: Arpan Dwivedi, Yogesh Pahariya

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In this paper, optimal design of hybrid standalone power supply system (SAPS) is done for off grid applications in remote areas where transmission of power is difficult. The hybrid SAPS system uses two primary energy sources, wind and solar, and in addition to these diesel generator is also connected to meet the load demand in case of failure of wind and solar system. This paper presents mathematical modeling of 1.4 MW hybrid SAPS system for rural electrification. This paper firstly focuses on mathematical modeling of PV module connected in a string, secondly focuses on modeling of permanent magnet wind turbine generator (PMWTG). The hybrid controller is also designed for selection of power from the source available as per the load demand. The power output of hybrid SAPS system is analyzed for meeting load demands at urban as well as for rural areas.

Keywords: SAPS, DG, PMWTG, rural area, off grid, PV module.

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Authors: jianhua Hou, Changqing Yang, and Beibo Qin

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A numerical method for solving nonlinear Fredholm integral equations of second kind is proposed. The Fredholm type equations which have many applications in mathematical physics are then considered. The method is based on hybrid function  approximations. The properties of hybrid of block-pulse functions and Chebyshev polynomials are presented and are utilized to reduce the computation of nonlinear Fredholm integral equations to a system of nonlinear. Some numerical examples are selected to illustrate the effectiveness and simplicity of the method.

Keywords: Hybrid functions, Fredholm integral equation, Blockpulse, Chebyshev polynomials, product operational matrix.

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Authors: P. Sateesh Kumar , S. Ramachandram

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Genetic Zone Routing Protocol (GZRP) is a new hybrid routing protocol for MANETs which is an extension of ZRP by using Genetic Algorithm (GA). GZRP uses GA on IERP and BRP parts of ZRP to provide a limited set of alternative routes to the destination in order to load balance the network and robustness during node/link failure during the route discovery process. GZRP is studied for its performance compared to ZRP in many folds like scalability for packet delivery and proved with improved results. This paper presents the results of the effect of load balancing on GZRP. The results show that GZRP outperforms ZRP while balancing the load.

Keywords: MANET, routing, ZRP, Genetic algorithm, GZRP, load balancing

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Authors: M. A. Sharbafi, M. Shakiba Herfeh, Caro Lucas, A. Mohammadi Nejad

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Several researchers have proposed methods about combination of Genetic Algorithm (GA) and Fuzzy Logic (the use of GA to obtain fuzzy rules and application of fuzzy logic in optimization of GA). In this paper, we suggest a new method in which fuzzy decision making is used to improve the performance of genetic algorithm. In the suggested method, we determine the alleles that enhance the fitness of chromosomes and try to insert them to the next generation. In this algorithm we try to present an innovative vaccination in the process of reproduction in genetic algorithm, with considering the trade off between exploration and exploitation.

Keywords: Genetic Algorithm, Fuzzy Decision Making.

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Authors: Branislav Vuksanović, Dragana Nikolić

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This paper describes the implementation and testing of a multichannel active noise control system (ANCS) based on the filtered-inverse LMS (FILMS) algorithm. The FILMS algorithm is derived from the well-known filtered-x LMS (FXLMS) algorithm with the aim to improve the rate of convergence of the multichannel FXLMS algorithm and to reduce its computational load. Laboratory setup and techniques used to implement this system efficiently are described in this paper. Experiments performed in order to test the performance of the FILMS algorithm are discussed and the obtained results presented.

Keywords: Active noise control, adaptive filters, inverse filters, LMS algorithm, FILMS algorithm.

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Authors: Mahmud Hesain ALdwaik, Omar Hsiain Eldwaik

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This paper deals with tracking and estimating time delay between two signals. The simulation of this algorithm accomplished by using Mathcad package is carried out. The algorithm we will present adaptively controls and tracking the delay, so as to minimize the mean square of this error. Thus the algorithm in this case has task not only of seeking the minimum point of error but also of tracking the change of position, leading to a significant improving of performance. The flowchart of the algorithm is presented as well as several tests of different cases are carried out.

Keywords: Tracking time delay, Algorithm simulation, Mathcad, MSE

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Authors: Moth'd Belal. Al-Daoud

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Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the k-means algorithm. Solutions obtained from this technique are dependent on the initialization of cluster centers. In this article we propose a new algorithm to initialize the clusters. The proposed algorithm is based on finding a set of medians extracted from a dimension with maximum variance. The algorithm has been applied to different data sets and good results are obtained.

Keywords: clustering, k-means, data mining.

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Authors: Ramin Javadzadeh, Emad Javadzadeh

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Locating the critical slip surface with the minimum factor of safety for a rock slope is a difficult problem. In recent years, some modern global optimization methods have been developed with success in treating various types of problems, but very few of such methods have been applied to rock mechanical problems. In this paper, use of hybrid model based on artificial immune system and cellular learning automata is proposed. The results show that the algorithm is an effective and efficient optimization method with a high level of confidence rate.

Keywords: CLA-AIS, failure surface, optimization methods, rock slope.

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Authors: Inderpreet Kaur, Neena Gupta

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Wavelength multiplexing (WDM) technology along with optical amplifiers is used for optical communication systems in S-band, C-band and L-band. To improve the overall system performance Hybrid amplifiers consisting of cascaded TDFA and EDFA with different gain bandwidths are preferred for long haul wavelength multiplexed optical communication systems. This paper deals with statistical analysis of different configuration of hybrid amplifier i.e. analysis of TDFA-EDFA configuration and EDFA – TDFA configuration. In this paper One-Way ANOVA method is used for statistical analysis.

Keywords: WDM, EDFA, TDFA, hybrid amplifier, One-wayANOVA.

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Authors: Anmari H. Viljamaa, Elina M. Varamäki

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In this study, we compare the profiles of transitory hybrid entrepreneurs and persistent hybrid entrepreneurs to determine how they differ. Hybrid entrepreneurs (HEs) represent a significant share of entrepreneurial activity yet little is known about them. We define HEs as individuals who are active as entrepreneurs but do no support themselves primarily by their enterprise. Persistent HEs (PHEs) are not planning to transition to fulltime entrepreneurship whereas transitory HEs (THEs) consider it probable. Our results show that THEs and PHEs are quite similar in background. THEs are more interested in increasing their turnover than PHEs, as expected, but also emphasize self-fulfillment as a motive for entrepreneurship more than PHEs. The clearest differences between THEs and PHEs are found in their views on how well their immediate circle supports full-time entrepreneurship, and their views of their own entrepreneurial abilities and the market potential of their firm. Our results support earlier arguments that hybrids should be considered separately in research on entrepreneurial entry and self-employment.

Keywords: Hybrid entrepreneurship, part-time entrepreneurship, self-employment, Theory of Planned Behavior.

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Authors: Heejung Lee, Hyo-Won Suh

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Hybrid knowledge model is suggested as an underlying framework for product development management. It can support such hybrid features as ontologies and rules. Effective collaboration in product development environment depends on sharing and reasoning product information as well as engineering knowledge. Many studies have considered product information and engineering knowledge. However, most previous research has focused either on building the ontology of product information or rule-based systems of engineering knowledge. This paper shows that F-logic based knowledge model can support such desirable features in a hybrid way.

Keywords: Ontology, rule, F-logic, product development.

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Authors: Vishnu Pratap Singh Kirar

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Artificial Neural Network (ANN) can be trained using back propagation (BP). It is the most widely used algorithm for supervised learning with multi-layered feed-forward networks. Efficient learning by the BP algorithm is required for many practical applications. The BP algorithm calculates the weight changes of artificial neural networks, and a common approach is to use a twoterm algorithm consisting of a learning rate (LR) and a momentum factor (MF). The major drawbacks of the two-term BP learning algorithm are the problems of local minima and slow convergence speeds, which limit the scope for real-time applications. Recently the addition of an extra term, called a proportional factor (PF), to the two-term BP algorithm was proposed. The third increases the speed of the BP algorithm. However, the PF term also reduces the convergence of the BP algorithm, and criteria for evaluating convergence are required to facilitate the application of the three terms BP algorithm. Although these two seem to be closely related, as described later, we summarize various improvements to overcome the drawbacks. Here we compare the different methods of convergence of the new three-term BP algorithm.

Keywords: Neural Network, Backpropagation, Local Minima, Fast Convergence Rate.

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Authors: R. Mahjoub, K. Maghsoudi Mehraban

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Since the heart of the hybrid system is the fuel cell and it has vital impact on efficiency and performance of cycle, in this study, the major modeling of electrochemical reaction within the fuel cell is analyzed. Also, solid oxide fuel cell is integrated with the gas turbine and thermodynamic analysis on different elements of hybrid system is applied. Next, in predefined operational points of hybrid cycle, the simulation results are obtained. Then, different source of irreversibility in fuel cell is modeled and influence of different major parameters on different irreversibility is computed and applied. Then, the effect of important parameters such as thickness and surface of electrolyte fuel cell are simulated in fuel cell and its dependency to these parameters is explained. At the end of the paper, different impact of parameters on fuel cell with a gas turbine and current density and voltage of fuel cell are simulated.

Keywords: Electrochemical analysis, Gas turbine, Hybrid system, Irreversibility analysis.

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Authors: Adel Bouchakhchoukha, Hakim Akeb

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In this work, we propose a hybrid heuristic in order to solve the Team Orienteering Problem (TOP). Given a set of points (or customers), each with associated score (profit or benefit), and a team that has a fixed number of members, the problem to solve is to visit a subset of points in order to maximize the total collected score. Each member performs a tour starting at the start point, visiting distinct customers and the tour terminates at the arrival point. In addition, each point is visited at most once, and the total time in each tour cannot be greater than a given value. The proposed heuristic combines beam search and a local optimization strategy. The algorithm was tested on several sets of instances and encouraging results were obtained.

Keywords: Team Orienteering Problem, Vehicle Routing, Beam Search, Local Search.

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Authors: Xiangbin Zhu

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EDF (Early Deadline First) algorithm is a very important scheduling algorithm for real- time systems . The EDF algorithm assigns priorities to each job according to their absolute deadlines and has good performance when the real-time system is not overloaded. When the real-time system is overloaded, many misdeadlines will be produced. But these misdeadlines are not uniformly distributed, which usually focus on some tasks. In this paper, we present an adaptive fuzzy control scheduling based on EDF algorithm. The improved algorithm can have a rectangular distribution of misdeadline ratios among all real-time tasks when the system is overloaded. To evaluate the effectiveness of the improved algorithm, we have done extensive simulation studies. The simulation results show that the new algorithm is superior to the old algorithm.

Keywords: Fuzzy control, real-time systems, EDF, misdeadline ratio.

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Authors: Xiaochuan Chen, Jianguo Yang, Beizhi Li

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Design for cost (DFC) is a method that reduces life cycle cost (LCC) from the angle of designers. Multiple domain features mapping (MDFM) methodology was given in DFC. Using MDFM, we can use design features to estimate the LCC. From the angle of DFC, the design features of family cars were obtained, such as all dimensions, engine power and emission volume. At the conceptual design stage, cars- LCC were estimated using back propagation (BP) artificial neural networks (ANN) method and case-based reasoning (CBR). Hamming space was used to measure the similarity among cases in CBR method. Levenberg-Marquardt (LM) algorithm and genetic algorithm (GA) were used in ANN. The differences of LCC estimation model between CBR and artificial neural networks (ANN) were provided. ANN and CBR separately each method has its shortcomings. By combining ANN and CBR improved results accuracy was obtained. Firstly, using ANN selected some design features that affect LCC. Then using LCC estimation results of ANN could raise the accuracy of LCC estimation in CBR method. Thirdly, using ANN estimate LCC errors and correct errors in CBR-s estimation results if the accuracy is not enough accurate. Finally, economically family cars and sport utility vehicle (SUV) was given as LCC estimation cases using this hybrid approach combining ANN and CBR.

Keywords: case-based reasoning, life cycle cost (LCC), artificialneural networks (ANN), family cars

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Authors: Peyman Naderi, Ali Farhadi, S. Mohammad Taghi Bathaee

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One of the best ways for achievement of conventional vehicle changing to hybrid case is trustworthy simulation result and using of driving realities. For this object, in this paper, at first sevendegree- of-freedom dynamical model of vehicle will be shown. Then by using of statically model of engine, gear box, clutch, differential, electrical machine and battery, the hybrid automobile modeling will be down and forward simulation of vehicle for pedals to wheels power transformation will be obtained. Then by design of a fuzzy controller and using the proper rule base, fuel economy and regenerative braking will be marked. Finally a series of MATLAB/SIMULINK simulation results will be proved the effectiveness of proposed structure.

Keywords: Hybrid, Driving, Fuzzy, Regeneration.

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Authors: Wullapa Wongsinlatam

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Back propagation algorithm (BP) is a widely used technique in artificial neural network and has been used as a tool for solving the time series problems, such as decreasing training time, maximizing the ability to fall into local minima, and optimizing sensitivity of the initial weights and bias. This paper proposes an improvement of a BP technique which is called IM-COH algorithm (IM-COH). By combining IM-COH algorithm with cuckoo search algorithm (CS), the result is cuckoo search improved control output hidden layer algorithm (CS-IM-COH). This new algorithm has a better ability in optimizing sensitivity of the initial weights and bias than the original BP algorithm. In this research, the algorithm of CS-IM-COH is compared with the original BP, the IM-COH, and the original BP with CS (CS-BP). Furthermore, the selected benchmarks, four time series samples, are shown in this research for illustration. The research shows that the CS-IM-COH algorithm give the best forecasting results compared with the selected samples.

Keywords: Artificial neural networks, back propagation algorithm, time series, local minima problem, metaheuristic optimization.

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Authors: Yongzhong Wu, Ping Ji

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This paper proposes a genetic algorithm based on a new replacement strategy to solve the quadratic assignment problems, which are NP-hard. The new replacement strategy aims to improve the performance of the genetic algorithm through well balancing the convergence of the searching process and the diversity of the population. In order to test the performance of the algorithm, the instances in QAPLIB, a quadratic assignment problem library, are tried and the results are compared with those reported in the literature. The performance of the genetic algorithm is promising. The significance is that this genetic algorithm is generic. It does not rely on problem-specific genetic operators, and may be easily applied to various types of combinatorial problems.

Keywords: Quadratic assignment problem, Genetic algorithm, Replacement strategy, QAPLIB.

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Authors: Hyen Ki Kim

Abstract:

This paper describes the design and implementation of cyber video consultation systems(CVCS) using hybrid P2P for video consultation between remote sites. The proposed system is based on client-server and P2P(Peer to Peer) architecture, where client-server is used for communication with the MCU(Multipoint Control Unit) and P2P is used for the cyber video consultation. The developed video consultation system decreases server traffic, and cuts down network expenses, as the multimedia data decentralizes to the client by hybrid P2P architecture. Also the developed system is tested by the group-type video consultation system using communication protocol and application software through Ethernet networks.

Keywords: Consultation, Cyber, Hybrid, Peer-to-Peer

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Authors: Jérôme Azé, Mathieu Roche, Yves Kodratoff, Michèle Sebag

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Term Extraction, a key data preparation step in Text Mining, extracts the terms, i.e. relevant collocation of words, attached to specific concepts (e.g. genetic-algorithms and decisiontrees are terms associated to the concept “Machine Learning" ). In this paper, the task of extracting interesting collocations is achieved through a supervised learning algorithm, exploiting a few collocations manually labelled as interesting/not interesting. From these examples, the ROGER algorithm learns a numerical function, inducing some ranking on the collocations. This ranking is optimized using genetic algorithms, maximizing the trade-off between the false positive and true positive rates (Area Under the ROC curve). This approach uses a particular representation for the word collocations, namely the vector of values corresponding to the standard statistical interestingness measures attached to this collocation. As this representation is general (over corpora and natural languages), generality tests were performed by experimenting the ranking function learned from an English corpus in Biology, onto a French corpus of Curriculum Vitae, and vice versa, showing a good robustness of the approaches compared to the state-of-the-art Support Vector Machine (SVM).

Keywords: Text-mining, Terminology Extraction, Evolutionary algorithm, ROC Curve.

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Authors: Hidehiko Okada

Abstract:

The author proposes an extension of particle swarm optimization (PSO) for solving interval-valued optimization problems and applies the extended PSO to evolutionary training of neural networks (NNs) with interval weights. In the proposed PSO, values in the genotypes are not real numbers but intervals. Experimental results show that interval-valued NNs trained by the proposed method could well approximate hidden target functions despite the fact that no training data was explicitly provided.

Keywords: Evolutionary algorithms, swarm intelligence, particle swarm optimization, neural network, interval arithmetic.

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Authors: Luciano Nieddu, Giuseppe Manfredi, Salvatore D'Acunto, Katia La Regina

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In this paper a non-parametric statistical pattern recognition algorithm for the problem of credit scoring will be presented. The proposed algorithm is based on a clustering k- means algorithm and allows for the determination of subclasses of homogenous elements in the data. The algorithm will be tested on two benchmark datasets and its performance compared with other well known pattern recognition algorithm for credit scoring.

Keywords: Constrained clustering, Credit scoring, Statistical pattern recognition, Supervised classification.

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Authors: Bi Kun, Gu Nai-jie, Tu Kun, Liu Xiao-hu, Liu Gang

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Traditional parallel single string matching algorithms are always based on PRAM computation model. Those algorithms concentrate on the cost optimal design and the theoretical speed. Based on the distributed string matching algorithm proposed by CHEN, a practical distributed string matching algorithm architecture is proposed in this paper. And also an improved single string matching algorithm based on a variant Boyer-Moore algorithm is presented. We implement our algorithm on the above architecture and the experiments prove that it is really practical and efficient on distributed memory machine. Its computation complexity is O(n/p + m), where n is the length of the text, and m is the length of the pattern, and p is the number of the processors.

Keywords: Boyer-Moore algorithm, distributed algorithm, parallel string matching, string matching.

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