Search Results - (( developing network selection algorithm ) OR ( java application learning algorithm ))
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition
Published 2010“…Furthermore, the dynamic Bayesian network's random variables are constituted from sets of lexical cues selected automatically by means of a variable length genetic algorithm, developed specifically for this purpose. …”
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Multi-Hop Selective Constructive Interference Flooding Protocol For Wireless Sensor Networks
Published 2019“…MSCIF integrates three main algorithms: clustering algorithm, selection algorithm, and a synchronized flooding. …”
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Optimal source substation location selection in radial distribution networks
Published 2004“…New computer algorithm has been developed to select the optimal location of source substation in radial distribution networks. …”
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Network reconfiguration and control for loss reduction using genetic algorithm
Published 2010“…Two selection methods that are used in Genetic Algorithm are the roulette wheel and tournament selections. …”
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Intelligent Multi-cellular Network Connectivity for Internet of Things Applications
Published 2023Conference Paper -
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques
Published 2024“…Fuzzy arithmetic operations on fuzzy numbers and artificial neural networks with a back-propagation learning algorithm were used to represent the structure of the neuro-fuzzy risk assessment model, whereas genetic algorithms were used to develop the safe path selection model. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks
Published 2022“…Following the best selection of neural network algorithm, BR algorithm is further trained using 50-70% training with 10-28 hidden neurons. …”
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Route Optimization System
Published 2005“…This algorithm is an exact algorithm that is specifically for finding the shortest route in a network. …”
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…However this feature selection algorithm might be unstable due to the stochastic property of GA. …”
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Implementation of a new Preference Based Final Year Project title selection system for undergraduate engineering students in UNITEN
Published 2023“…Three algorithms were developed for this allocation purpose, and they were evaluated by calculation and comparison of the costs of their selection. …”
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Resource allocation in coordinated multipoint long term evolution-advanced networks
Published 2015“…The CLD-ORA algorithm has further enhanced the LRA and ORA algorithms with network sum-rate improvement of 77% and 33%, respectively. …”
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Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network
Published 2021“…To achieve those objectives, there were three main phases implemented in the network development framework; first, the determination of feature extraction using multiway principal component analysis (MPCA), second, the ANN model development and architecture selection for BOD and COD analysis, and third, the ANN architecture selection for WQI prediction model. …”
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Monograph