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Register allocation is one of most important compiler optimization techniques. The most famous method for register allocation is graph coloring and the solution presented in this paper (RAGCES) is based on the graph coloring too; for coloring interference graph, evolutionary algorithm is used. In this method graph coloring and selecting variables for spilling is taken place at the same time. This...
Internet is the biggest source of data and information today. It is the family of web sites and informative files. This paper focuses mainly on the web data and proposes some conceptual theories to extract knowledge through different web mining techniques like Clustering,FIS,ANN,LGP etc. We also focused on various aspects of applications of web mining in E-commerce & Business Intelligence. Finally,...
During the learning process, every agent’s action affects the interaction with the environment based on the agent’s current knowledge and future knowledge. The agent must therefore have to choose between exploiting its current knowledge or exploring other alternatives to improve its knowledge for better decisions in the future. This paper presents critical analysis on a number of exploration strategies...
In this paper, a Harmony Search Algorithm (HSA) is adapted for Nurse Rostering Problem (NRP). HSA is a global optimization method derived from a musical improvisation process which has been successfully tailored for several optimization domains. NRP is a hard combinatorial scheduling problem of assigning given shifts to given nurses. Using a dataset established by International Nurse Rostering Competition...
The QoS multicast routing problem is to find a multicast routing tree with minimal cost that can satisfy constraints such as bandwidth, delay, delay jitter and loss rate. This problem is NP Complete. In this paper, we present a swarming agent based intelligence algorithm using a hybrid Ant Colony Optimization/Particle Swarm Optimization (ACO/PSO) algorithm to optimize the multicast tree. The algorithm...
Software testing is meant to increase confidence in the correctness of software. Due to time, cost and other resource constraints, manual testing is highly impractical and undesirable, especially for the increasingly large sized software being developed these days. Therefore, there is a need to automate the testing process. This calls for the development of a time-efficient technique to automatically...
Protein-protein interactions (PPI) form the core part of the entire interatomic system for all the living elements. In this article, the role of different Gene Ontology(GO)-based semantic similarity measures in predicting PPIs have been explored. To find out a relevant subset of semantic similarity measures, a feature selection approach is developed with Angle Modulated Differential Evolution(AMDE),...
This paper studies the impact of varying the population’s size and the problem’s dimensionality in a parallel implementation, for an NVIDIA GPU, of a canonical GA. The results show that there is an effective gain in the data parallel model provided by modern GPU’s and enhanced by high level languages such as OpenCL. In the reported experiments it was possible to obtain a speedup higher than 140 thousand...
Selection of players for a high performance cricket team within a finite budget is a complex task which can be viewed as a constrained multi-objective optimization problem. In cricket team formation, batting strength and bowling strength of a team are the major factors affecting its performance and an optimum trade-off needs to be reached in formation of a good team. We propose a multi-objective approach...
Being one of the main challenges to clustering algorithms, the sensitivity of fuzzy c-means (FCM) and hard c-means (HCM) to tune the initial clusters centers has captured the attention of the clustering communities for quite a long time. In this study, the new evolutionary algorithm, Harmony Search (HS), is proposed as a new method aimed at addressing this problem. The proposed approach consists of...
Motion planning of a robotic arm has been an important area of research for the last decade with the growing application of robot arms in medical science and industries. In this paper the problem of motion planning has been dealt with in two stages, first by developing appropriate cost functions to determine a set of via points and then fitting an optimal energy trajectory. Lbest Particle Swarm Optimization...
Minimum dominating set, which is an NP-hard problem, finds many practical uses in diverse domains. A greedy algorithm to compute the minimum dominating set is proven to be the optimal approximate algorithm unless P = NP. Meta-heuristics, generally, find solutions better than simple greedy approximate algorithms as they explore the search space better without incurring the cost of an exponential algorithm...
In this article, an evolutionary metaheuristic algorithm known as the Invasive Weed Optimization (IWO) is applied for automatically partitioning a dataset without any prior information about the number of naturally occurring groups in the data. The fitness function used in the genetic algorithm is a cluster validity index. Depending on the results of this index IWO returns the segmented dataset along...
The extraction of hidden predictive information from large databases is possible with data mining. Anemia is the most common disorder of the blood. Anemia can be classified in a variety of ways, based on the morphology of RBCs, etiology, etc . In this paper we present an analysis of the prediction and classification of anemia in patients using data mining techniques. The dataset constructed from complete...
Taboo evolutionary programming (TEP) is a novel evolutionary programming technique found extensive usage in the present decade. The algorithm can be implemented in many complex problems in science and technology to find the optimum solutions with constraints. In this paper, we studied a two-point boundary value problem such as Lambert conic determination to find out the optimum impulsive requirements...
In order to solve the real-world problem which named Cleveland heart disease classification problem, we used a new stochastic optimization algorithm that simulate the plant growing process. It employs the photosynthesis operator and phototropism operator to mimic photosynthesis and phototropism phenomenons, we call it briefly with APPM algorithm. For the plant growing process, photosynthesis is a...
Wireless Sensor Networks consist of wide range of applications to be discerned and researched nowadays. The foremost restraint of these Networks is to reduce energy consumption and to prolong the lifetime of the network. In this paper a meta-heuristic optimization technique, Cuckoo Search is used to aggregate data in the Sensor Network. In the proposed technique, the least energy nodes are formed...
A new efficient optimization method, called ‘Teaching–Learning-Based Optimization (TLBO)’, has been proposed very recently for the optimization of mechanical design problems. This paper proposes a new approach to using TLBO to cluster data. It is shown how TLBO can be used to find the centroids of a user specified number of clusters. The new TLBO algorithms are evaluated on some datasets and compared...
Many methods were proposed to generate a large number of association rules efficiently. These methods are dependent on non-semantic information such as support, confidence. Also work on pattern analysis has been focused on frequent patterns, sequential patterns, closed patterns. Identifying semantic information and extracting semantically similar frequent patterns helps to interpret the meanings of...
Machine learning tools are employed to establish relationship between the characteristics of protein-ligand binding site and enzyme class. Enzyme classification is a challenging problem from data mining perspective due to (i) class imbalance problem and (ii) appropriate feature selection. We address the problem by choosing novel features from protein binding site. Protein Ligand Interaction Database...
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