Search Results - (( simulation optimization approach algorithm ) OR ( using function sensor algorithm ))
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1
A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…Background and Objectives: Magnificent localization precision and low operating expenses are the main keys and essential issues to managing and operating outdoor wireless sensor networks. This work proposes a novel and rigorous efficiency localization algorithm utilizing a simplex optimization approach for node localization. …”
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Article -
2
Sensor Node Placement in Wireless Sensor Network Using Multi-objective Territorial Predator Scent Marking Algorithm
Published 2023“…Simulation results show that WSN deployed using the MOTPSMA sensor node placement algorithm outperforms the performance of the other two algorithms in terms of coverage, connectivity and energy usage. © 2014 King Fahd University of Petroleum and Minerals.…”
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3
WSN sensor node placement approach based on multi-objective optimization
Published 2023“…A sensor node placement algorithm that utilizes Multi-objective Territorial Predator Scent Marking Algorithm (MOTPSMA) is presented in this paper. …”
Conference Paper -
4
A wireless interference-aware internet-of-things gateway placement framework with genetic algorithm approach
Published 2022“…The framework generates the solution using genetic algorithm. Our experimental results show that solution can be generated with relatively low processing power even for a relatively wide search space. …”
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Final Year Project / Dissertation / Thesis -
5
Multi-objective Optimization (MOO) approach for sensor node placement in WSN
Published 2023“…The MOO approach of TPSMA (MOTPSMA) deployed in this paper uses the minimum energy consumption and maximum coverage as the objective functions while the single objective approach TPSMA only considers maximum coverage. …”
Conference paper -
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WSN sensor node placement approach using Territorial Predator Scent Marking Algorithm (TPSMA)
Published 2023“…The TPSMA deployed in this paper uses the minimum uncovered area as the objective function. …”
Conference paper -
7
PID-PSO DC motor position controller design for ankle rehabilitation system
Published 2023“…The control algorithms also aim to be analyzed using an incremental rotary encoder sensor device as closed-loop feedback for dorsiflexion and plantarflexion movement. …”
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Thesis -
8
Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…The contribution of this work is to optimize the base of Fuzzy membership function of the APFLC by using GA technique. …”
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Thesis -
9
Non-weighted aggregate evaluation function of multi-objective optimization for knock engine modeling
Published 2017“…It also aims to optimize the nonlinear nature of the factors by using Genetic Algorithm (GA) as well as investigate the behavior of such function. …”
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10
Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems
Published 2023“…The selection of proper CHs using metaheuristic algorithms fnds useful in design of energy-efcient WSNs. …”
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Article -
11
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Thesis -
12
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…A new meta-heuristic optimization technique called the Slime Mould Algorithm (SMA) approach has a high convergence rate or a few iterations and superior optimization indices analyzed against other algorithms. …”
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13
Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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14
Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm
Published 2016“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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Conference or Workshop Item -
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A multiobjective simulated Kalman filter optimization algorithm
Published 2018“…This paper presents a new multiobjective type optimization algorithm known as a Multiobjective Optimization Simulated Kalman Filter (MOSKF). …”
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Conference or Workshop Item -
16
A Kalman Filter Approach for Solving Unimodal Optimization Problems
Published 2015“…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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17
A noble approach of ACO algorithm for WSN
Published 2018“…The proposed algorithm has been simulated and verified utilizing MATLAB and the simulation results demonstrate that new ant colony optimization based algorithm can achieve better performance and faster convergence to determine the best cost route.…”
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Proceeding Paper -
18
An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach
Published 2017“…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
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Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems
Published 2016“…However, the SKF is only capable to solve continuous numerical optimization problem. In order to solve discrete optimization problems, the SKF algorithm is combined with an angle modulated approach. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In this research, two novel estimation-based metaheuristic optimization algorithms, named as Simulated Kalman Filter (SKF), and single-solution Simulated Kalman Filter (ssSKF) algorithms are introduced for global optimization problems. …”
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