Search Results - (( based solution learning algorithm ) OR ( using simulation modified algorithm ))
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1
Adaptive beamforming algorithm based on Simulated Kalman Filter
Published 2017“…A modified version of the SKF algorithm, named Opposition-Based SKF (OBSKF), introduced by K. …”
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2
A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…The proposed algorithm is scrutinized and validated using the modified IEEE 30-bus test system. …”
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3
A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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4
Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem
Published 2022“…Simulated Kalman Filter (SKF) solves optimization problems by finding the estimate of the optimum solution. As a multi-agent algorithm, every agent in the population acts as a Kalman filter by using a standard Kalman filter framework, which includes a simulated measurement process and a best-so-far solution as a reference. …”
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5
Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization
Published 2011“…In this study, the CSA is modified using the best solution for each exposure (iteration) namely Single Best Remainder (SBR) CSA. …”
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6
Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers
Published 2022“…OPF is one of the well-known problems in power system operations and with the inclusion of the FACTS devices allocation problems into OPF will make the solution more complex. Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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7
Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia
Published 2015“…The selection is based on the user preferences since it uses a self-learning algorithm to determine triggers and handover thresholds dynamically. …”
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8
The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…It’s data-driven, self-adaptive, and non-linear capabilities channel it for use in processing at high speed and ability to learn the solution to a problem from a set of examples. …”
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9
Optimized clustering with modified K-means algorithm
Published 2021“…Testing on real data sets showed consistency results as the simulated ones. Generally, the proposed modified k-means algorithm is able to determine the optimum number of clusters for huge data.…”
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10
Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm
Published 2012“…This document is a study about LEACH algorithm where the implementation was done using OMNeT++ network simulator to study the performance of this algorithm in term of network lifetime. …”
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11
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Firstly, an architecture for the clustering ensemble based on incremental genetic-based algorithms is proposed consisting of two phases: (i) to produce cluster partitions as initial populations, (ii) to combine cluster partitions and to generate final clustering solution by incremental genetic based clustering ensemble learning algorithm. …”
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12
A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and Swap Operator
Published 2021“…The simulated Kalman filter (SKF) is an algorithm for population-based optimization based on the Kalman filter framework. …”
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13
1D Multigrid Solver For Finite Element Method
Published 2022“…The new algorithm also has been tested using time simulation. …”
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14
Comparison of path planning in simulated robot
Published 2020“…There are 4 path planning algorithms will be compared, which are Dijkstra’s algorithm, A* algorithm, RapidExploring Random Tree (RRT) algorithm, and the last one is an algorithm modified from A*. …”
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15
Estimation of the denitrification in the lower Mississippi Valley
Published 2001“…The CREAMS denitrification algorithm was modified to account for the high soil moisture conditions by incorporating a water function.The average annual denitrification value simulated by using modified algorithm was higher than the one predicted by CREAMS algorithm.This result is expected because the modified algorithm uses a water function to reflect the degree of soil saturation.…”
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16
PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…Nonetheless, OBL-based solutions often consider one particular direction of the opposition. …”
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…These two adaptive routing algorithms enhance the existing Confidence-based Q (CQ) and Confidence-based Dual Reinforcement Q (CDRQ) Routing Algorithms. …”
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Dynamic obstacle handling in multi-robot coverage
Published 2024“…The impacts of the modified algorithm’s parameters on simulation results were also studied to determine the optimal parameters for achieving better performance. …”
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Final Year Project / Dissertation / Thesis
