Search Results - (( based optimization based algorithm ) OR ( step function sensor algorithm ))
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1
Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors
Published 2010“…The image reconstruction algorithm was based on the gradient minimization of an augmented cost function defined as the difference between measured and calculated fields. …”
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2
Predictive analytics of Junctionless Double Gate Strained MOSFET using genetic algorithm with doe-based grey relational analysis
Published 2023“…Finally, the genetic algorithm is utilized to predict the optimum level of design parameters based on the derived objective function. …”
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Hybrid metaheuristic method for clustering in wireless sensor networks / Bryan Raj Peter Jabaraj
Published 2023“…As such, this thesis proposes a hybrid metaheuristic method that consists of Sperm Swarm Optimization (SSO) algorithm and Genetic Algorithm (GA), which is termed HSSOGA. …”
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4
PREDICTIVE ANALYTICS OF JUNCTIONLESS DOUBLE GATE STRAINED MOSFET USING GENETIC ALGORITHM WITH DOE-BASED GREY RELATIONAL ANALYSIS
Published 2024“…Finally, the genetic algorithm is utilized to predict the optimum level of design parameters based on the derived objective function. …”
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Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…Most of the existing algorithms consider the noise filtering step precedes trajectory segmentation step which mean that there is no preprocessing method to partition trajectory into set of segments and remove noise points in real time with low computational cost. …”
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6
Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter
Published 2013“…As a simulation study, we applied the algorithms in a network to track the position and speed of a projectile and compared the results with real world circumstances, using the concept of transient mean square deviations of network as a cost function. …”
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7
Arduino solar tracker with blynk / Muhammad Azim Hafizi Azlan
Published 2024“…The system maximizes solar energy capture by ensuring correct panel alignment in real-time through the use of servo motors, light sensors, and an intelligent algorithm. The Arduino board serves as the main control unit, coordinating panel movements and allowing online or mobile application-based remote monitoring and control. …”
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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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9
Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The fault detection algorithm identifies the time and location of each fault. …”
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10
A contactless computer vision system for underwater walking and jogging gait analysis using YOLO-pose and Multi-CNN BiLSTM architecture
Published 2025“…A comparison of hyperparameter optimization algorithms was conducted, with the combination of multivariate tree-structured Parzen estimators (MultiTPE) and Hyperband identified as the optimal approach. …”
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Improved static and dynamic FBG sensor system for real-time monitoring of composite structures
Published 2017“…Thus, the designation of this research study is to improve the current FBG based real-time monitoring system with the use of certain functions and algorithms, that are the instant mesh-grid function, voltage normalization algorithm, CC-LSL algorithm, and FFT function. …”
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12
Widely linear dynamic quaternion valued least mean square algorithm for linear filtering
Published 2017“…Choosing the right value of step size is very important for the adaptation process of the algorithm. …”
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13
Opposition-based Whale Optimization Algorithm
Published 2018“…In order to improve solution accuracy and reliability, this paper proposes a new algorithm based on WOA. The new algorithm called Opposition-based Whale Optimization (OWOA). …”
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14
Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…To overcome these drawbacks and to achieve an appropriate percentage of exploitation and exploration, this study presents a new modified teaching learning-based optimization algorithm called the fuzzy adaptive teaching learning-based optimization algorithm. …”
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15
Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
Published 2015“…In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. …”
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16
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…Finally, a crowding distance and non-dominated-sorting-based multi-objective hybrid firefly & particle swarm optimization (MOHFPSO) algorithm is designed for MOOPF problems. …”
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17
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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18
Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network
Published 2020“…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
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19
Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm
Published 2024“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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