Search Results - (( user evaluation bat algorithm ) OR ( user identification path algorithm ))
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Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm
Published 2022“…This research will conduct comparison of hybrid Genetic Algorithm and Bat Algorithm (GA-BA) with Genetic Algorithm (GA) and Bat Algorithm (BA). …”
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Academic Exercise -
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Localization using fingerprint method in emergency situation for indoor navigation system / Felix Ceilomond Samam
Published 2015“…Route planning using Dijkstra's algorithm can produce better accuracy and more reliable in indoor environment since the only factor taken into account is the weight for each path.…”
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Exploratory Study on Navigation System for Visually Impaired Person
Published 2013“…Path planning algorithm will be implemented in this project to give the shortest path and direction as a navigation guide for visually impaired people. …”
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Systematic design of chemical reactors with multiple stages via multi-objective optimization approach
Published 2015“…Specifically, multi-objective optimization method will be used to generate Pareto optimal solutions that characterize the non-inferior solutions set for the problem. Following the identification of path-dependent design variables, several (possibly conflicting) design objectives will be selected and solutions of the corresponding problem will be generated from multi-objective optimization algorithm. …”
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Conference or Workshop Item -
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Performance Study of Developed SMART EYE for Visually Impaired Person.
Published 2013“…Path planning algorithm will be implemented in this project to give the shortest path and direction as a navigation guide for visually impaired people. …”
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Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff
Published 2017“…In terms of number of users in the cell, the algorithm could achieve up to 240% of maximum throughput, 61% reduction in ECR and 150% improvement in EE. …”
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Efficient relay placement algorithm using landscape aware routing (erpalar)
Published 2011“…Chromosome in GA-2 is the AP, and user slots on the AP as genes. Since this algorithm win be used at different deployment sites, a crossover rate of 0.5 is recommended for both GA-I and GA-2; and mutation rate of 0.1 for GA-l and GA-2. …”
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Thesis
