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Support Vector Machine (SVM) is a useful technique for data classification with successful applications in different fields of bioinformatics, image segmentation, data mining, etc. A key problem of these methods is how to choose an optimal kernel and how to optimize its parameters in the learning process of SVM. The objective of this study is to propose a Genetic Algorithm approach for parameter optimization...
Web sites may contain numerous documents. Using some web techniques, it's possible to analyze users' data about using resources, contents of those documents and structure of web sites. Adaptive web sites automatically change their structure and representation based on visitor's behavior. Shortcutting is an approach that enables connecting two documents which has never been connected before. Most of...
Construction of underground natural gas storage is a large, complex, with multi-objective nature of the projects. Vague Sets Based on Underground Gas Storage solution design are optimized. Examples show that it is convenient and feasible. Proposed single-value data into the data of the formula Vague, Vague sets introduce new similarity measures between the new formula, these two types of formula as...
In view of current characteristics of well drilling support system, analyzing mass of well history data, logging data and drilling materials of each oil field in China, a new scheme optimization method is established using comprehensive comparison and analysis of multi-well data. The new method is successfully applied to a distributed drilling support system that uses network and computer as operation...
For the retailing, the shelf space allocation is a key issue which impacts on the retailer's product sales and profits directly. For the small-scale supermarket, due to the small store and the product variety, the traditional “format style” shelf space layout is not appropriate. To solve this problem, a shelf space allocation solution based on data mining techniques is proposed in this paper. With...
Fuzzy clustering is an important problem which is the subject of active research in several real world applications. Fuzzy c-means (FCM) algorithm is one of the most popular fuzzy clustering techniques because it is efficient, straightforward, and easy to implement. However FCM is sensitive to initialization and is easily trapped in local optima. Particle swarm optimization (PSO) is a stochastic global...
Automatic cell sorting and isolation for recovery of such live cells, mostly microorganisms, is a challenging task. Lab-on-a-chip devices implemented as cell arrays are used for this purpose. For an abstract model of the problem, we can assume the cell array to be represented by a matrix where each cell can be any of the three types: empty, good (or desired) and bad (or undesired). The problem is...
Motivated by the growing demand of accuracy and low computational time in optimizing functions in various fields of engineering, an approach has been presented using the technique of parallel computing. The parallelization has been carried out on one of the simplest and flexible optimization algorithms, namely the particle swarm optimization (PSO) algorithm. PSO is a stochastic population global optimizer...
Particle Swarm Optimization (PSO) algorithms represent a new approach for optimization. In this paper image enhancement is considered as an optimization problem and PSO is used to solve it. Image enhancement is mainly done by maximizing the information content of the enhanced image with intensity transformation function. In the present work a parameterized transformation function is used, which uses...
In this paper design of multiplier-less nonuniform filterbank transmultiplexer (ML NUFB TMUX) is presented. Nonuniform filter bank transmultiplexer (NUFB TMUX) is preferred when applications with different data rates are to be multiplexed. If filter coefficients can be represented in canonic signed digit (CSD) format with minimum number of signed power of two (SPT) terms, hardware complexity can be...
This paper presents a new particle swarm optimization based corrective strategy to alleviate overloads of transmission lines. A direct acyclic graph (DAG) technique for selection of participating generators and buses with respect to a contingency is presented. Particle swarm optimization (PSO) technique has been employed for generator rescheduling and/or load shedding problem locally, to restore the...
A general new methodology using evolutionary algorithm viz., Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi Objective Particle Swarm Optimization (MOPSO) for obtaining optimal tolerance allocation and alternative process selection for mechanical assembly is presented. The problem has a multi-criterion character in which 3 objective functions, 6 constraints and 11 variables are...
Optimization problems are ubiquitous and consequential. In fact every sphere of human activity that can be quantified can be formulated as an optimization problem. The focus of this work is on Global Optimization which is not only desirable but also necessary in many cases. In the past few decades several Global optimization algorithms have been suggested in literature out of which stochastic, population...
The K-Modes algorithm is one of the most popular clustering algorithms in dealing with categorical data. But the random selection of starting centers in this algorithm may lead to different clustering results and falling into local optima. In this paper we proposed a swarm-based K-Modes algorithm. The experimental results over two well known Soybean and Congressional voting categorical data sets show...
Evolutionary Algorithms are inspired by biological and sociological motivations and can take care of optimality on rough, discontinuous and multimodal surfaces. During the last few decades, these algorithms have been successfully applied for solving numerical bench mark problems and real life problems. This paper presents the application of two popular Evolutionary Algorithms (EA); namely Particle...
Research in the area of optimizing databases in any Database Management System (DBMS) has been evolving constantly. Today, programming languages are being integrated into database systems to help professional programmers develop software quickly to meet deadlines. Therefore, the design of a database must cater to both the needs of customers and the efficiency of database processes. In this paper,...
Proximity ranking according to end-to-end network distances (e.g., Round-Trip Time, RTT) can reveal detailed proximity information, which is important in network management and performance diagnosis in distributed systems. However, to the best of our knowledge, there has been no similar work on this subject in the P2P computing field. We present a distributed rating method iRank, that enables proximity...
Massive multiuser virtual environments (MMVEs) and the idea of a global scale 3D Web have grown popular in recent years. While commercial precursors of such environments for the most part rely on centralized client/server architectures, it is commonly accepted that a global scale virtual online world can only be realized in a distributed fashion. Within the HyperVerse project, we have developed and...
The weapon target assignment problem can be modeled as an optimization problem in which the objective is to assign weapons to target in order to maximize the optimum target damage value. The mathematical model of the problem is subject to various constraints depending on the availability of weapons The objective function of the problem is non linear and the constraints are linear in nature. Also,...
In video-fluoroscopic swallowing assessment the time taken for the bolus material to transit the oral and pharyngeal regions is currently estimated by visual inspection. This paper presents an effective method for objectively approximating these timings by fitting a Gaussian surface to the first derivative of the intensity profiles along user defined anatomical boundaries. The profile characteristics...
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