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This paper discusses the performance evaluation of the Content Based Image Retrieval (CBIR) system using the optimality in selection of feature vector elements. The performance of the CBIR system may be improved by appropriate analysis of the image. Image analysis is still facing problems related to the detection of the objects. In spite of the noticeable achievements using the part based model, the...
Two evolutionary algorithms are proposed in this paper to handle with access point channel assignment in Wireless Local Area Network. The objective considered is to minimize the maximum level of interference experienced by the users. Two deterministic heuristics, commonly employed in the considered problem, are used as benchmark. The paper is focused on the IEEE 802.11ac standard, which operates exclusively...
Condition monitoring is a vital task in the maintenance of industry machines. This paper proposes a reliable condition monitoring method using a genetic algorithm (GA) which selects the most discriminate features by taking a transformation matrix. Experimental results show that the features selected by the GA outperforms original and randomly selected features using the same k-nearest neighbor (k-NN)...
We address the permutation flow shop scheduling problem with sequence dependent setup times between jobs. Each job has its weight of importance as well as due date. The goal is to find sequence of jobs such that total weighted tardiness of jobs is minimized. Due to NP-Hard complexity of this problem, a hybrid meta-heuristic algorithm based on Harmony Search Algorithm is developed. In the proposed...
Clustering is an unsupervised classification method where objects in the unlabeled data set are classified on the basis of some similarity measure. The conventional partitional clustering algorithms, e.g., K-Means, K-Medoids have several disadvantages such as the final solution is dependent on initial solution, they easily stuck into local optima. The nature inspired population based global search...
We studied the joint replenishment problem with deterministic resource restriction. A differential evolution (DE) algorithm that uses indirect grouping strategy to solve constrained joint replenishment is presented. The procedure and structure of the DE algorithm is proposed. Extensive computational experiments are performed to compare the performances of the DE algorithm with results of genetic algorithm...
In this paper, we propose a multi-task scheduler by considering the underwater risk assessment for autonomous underwater vehicle. We divide the task scheduler into two parts: a path coordinator and a condition interpreter. The path coordinator finds the minimum cost sequence from several combinations of paths by using a genetic algorithm. The condition interpreter limits high risk paths such as obstacle...
For the control of robots, like bipedal robots, an accurate system model with the corresponding inertial parameters can enhance the performance of the control algorithms significantly. This paper presents a convenient method for identification of the static inertial parameters with minimal sensor effort. Next to the identification method itself an approach for the calculation of optimal exciting identification...
Random Forest RF is an ensemble learning approach that utilises a number of classifiers to contribute though voting to predicting the class label of any unlabelled instances. Parameters such as the size of the forest N and the number of features used at each split M, has significant impact on the performance of the RF especially on instances with very large number of attributes. In a previous work...
Self-organizing map (SOM), an unsupervised learning way of artificial neural network, plays a very important role for classification and clustering of inputs. The property of SOM, also called topology-preserving maps or self-organizing feature map (SOFM), is observed in human brain which is not found in other artificial neural networks. Aircrafts' crossing points between two airports may generate...
Query is one of the most important factors that can directly influence the results of information retrieval (IR). However, the query is defined by the user and thus inevitably has the following two problems: (1) the user often cannot exactly represent their search intention via query terms, (2) the user cannot effectively select the weight of each query term based on its importance toward the query's...
This paper presents a multi-objective particle swarm optimization with asynchronous update (AS-MOPSO). That is, Pareto front is immediately evaluated whenever a particle in the swarm updates, a subsequent particle in the swarm regulates its position partly based on information up to current iteration, and partially depending on previous message. To evaluate the features of the proposed algorithm,...
How to reduce energy consumption under the restraints of satisfying customer service level by effective resource allocation and scheduling has become a key issue in cloud computing. In this paper, we propose a new resources-allocation and scheduling architecture for energy consumption optimization. Based on this architecture, a new energy consumption optimization model is designed to meet the real-time...
Search engines resolve the most informational needs of users by indexing huge amounts of data from web pages. In this process, spam pages prevent users from reaching their desirable results. Spam pages use deceptive methods to get a higher rank than their real one in search engines. For a human expert, recognition of spam pages is an easy task, but it is too complicated for a machine. Regarding the...
Petri nets are graph based tools to model and study concurrent systems and their properties; one of them is liveness, which is related to the possibility of every part of the system to be activated eventually. Siphons are sets of places that are related to liveness properties. When we need to deal with realistic problems its computation is hard or even impossible and this is why in this paper we are...
Unit Commitment Problem (UCP) is a high-dimensional, discrete and non-linear optimization problem which is complicated so that it is difficult to find the optimal solution. This paper proposes a new method, called improved priority differential evolution (IPDE), based on differential evolution algorithm and priority calculation to solve UCP. We increased the speed of convergence and the accuracy of...
This paper proposes a new method for computing the spectrum of a periodic analog signal, based on the concept of minimizing a square error function. The method involves generating the error function, which is accomplished using symbolic computation with the program Maple, and the minimization of this function using the genetic algorithms and gradient methods using the program Matlab.
This article proposes a new dynamic planning navigation strategy for use with mobile terrestrial robots. The strategy was applied to situations in which the environment and obstacles were unknown. After each displacement event, the robot replanned its route using a control algorithm that minimized the distance to the target and maximized the distance between the obstacles. Using a spatial localization...
In this paper time modulation technique is implied to linear antenna array. The evolutionary optimization algorithm like real coded genetic algorithm (RGA) and particle swarm optimization (PSO) is used to get the optimal radiation pattern by controlling the switching time sequence of each element of the array. The time modulation period is divided into numerous minimal time steps, where the ON-OFF...
We address here a large scale routing and scheduling transportation problem, through introduction of a flow model designed on a dynamic network. We deal with this model while using a master/slave decomposition scheme, and testing the behavior on this scheme of both a GRASP algorithm and a Genetic algorithm.
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