Search Results - (( developing initial evolution algorithm ) OR ( java applications tree algorithm ))
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Chaotic map initializations with Tiki-Taka algorithm for software remodularization problem
Published 2021“…Addressing this issue, this paper evaluates the performance of automated software remodularization using the newly developed Tiki-Taka Algorithm (TTA) and its variants with four chaotic map initializations based on Chebyshev map, Circle map, Logistic Map and Piecewise Map. …”
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An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
Published 2018“…In comparison with V-Detectors, cuckoo search, differential evolution, support vector machine, artificial neural network, na¨ıve bayes, and k-NN, experimental results demonstrates that CSDE-V-Detectors outperforms other algorithms with an average detection rate of 95:30% on all the datasets. …”
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Thesis -
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…The main contention of this thesis is to investigate the development of new optimization technique based on Differential Evolution algorithm (DE), applied for radar signal denoising application. …”
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Efficient radio resource management algorithms for downlink long term evolution networks
Published 2018“…Our algorithms prolong the battery life by adjusting the base station using initial and final states. …”
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Mining Sequential Patterns using I-PrefixSpan
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Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE)
Published 2015“…Purpose – The purpose of this paper is to develop a multiobjective differential evolution (MODE)-based extended H-infinity controller for autonomous helicopter control. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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A hybrid SP-QPSO algorithm with parameter free adaptive penalty method for constrained global optimization problems
Published 2018“…This paper attempts the suitability of newly developed hybrid algorithm, Shuffled Complex Evolution with Quantum Particle Swarm Optimization abbreviated as SP-QPSO, extended specifically designed for solving constrained optimization problems. …”
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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Proposed algorithm for scheduling in computational grid using backfilling and optimization techniques
Published 2016“…To allocate the suitable resources for the incoming jobs, a scheduling algorithm has to manage this process.In this paper, we provide a critical review the recent mechanisms in “grid computing” environment.In addition, we propose a new scheduling algorithm to minimize the delay for the end user, Gap Filling policy will be applied to improve the performance of the priority algorithm.Then, an optimization algorithm will perform in order to further enhance the initial result for that obtained from backfilling mechanism.The main aim of the proposed scheduling mechanism is to improve the QoS for the end user in a real grid computing environment.…”
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Nonlinear modeling and control of a spark ignition engine idle speed / Hazem Mohamed
Published 1998“…The fuzzy controller is formulated as a radial basis function network trained by the orthogqnalleast squares algorithm to estimate the controller parameters. The train~ng data of the network is the entries of an optimal control table derived by analyzing the evolution of the state trajectories of the system under different initial conditions using the cell to cell mapping technique. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. The general idea of I-PrefixSpan is to use the efficient data structure for general tree-like framework and separator database to reduce the execution time and memory usage. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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Solving an application of university course timetabling problem by using genetic algorithm
Published 2022“…Among the approaches, genetic algorithm (GA), constructed based on Darwin's theory of evolution, becomes the renowned approach to solve various types of timetabling problems. …”
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…We utilized eight robust machine learning algorithms to analyze this dataset. We found that the Decision tree classifier had the best performance, out of the eight algorithms, with an accuracy of 87%. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat
Published 2021“…The iterative nature of KMeans and random initialization of centroids which leads the algorithm to stick in a local optimum and unable to converge to optimum results, are another weakness. …”
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Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images
Published 2016“…The enhanced contrast image is further optimized by the particle swarm optimization algorithm. Thereafter, the optimized image is processed by the Chan-Vese method to extract the ATFL region through curve evolution; then the resultant image smoothed by morphological operation. …”
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