Search Results - probable evaluation ((((method algorithm) OR (search algorithm))) OR (path algorithm))
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…In the benchmarking of the SKF and ssSKF algorithms’ performance in solving the 14-hole PCB drill path optimization case study with recent implementations, on average, both algorithms show the ability to converge to the optimal solution at a smaller number of function evaluations compared to the Gravitational Search Algorithm (GSA), Cuckoo Search (CS), and Intelligent Water Drop (IWD), although fall-short to the Taguchi- Genetic Algorithm optimization algorithm.…”
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Design of A unmanned aerial vehicles assisted search and rescue collaboration architecture for emergency communication systems / Abdu Ahmed Saif Ahmed
Published 2022“…The multi-UAV and SAR collaboration have been evaluated based on average capacity, energy efficiency, line-of-sight probability, path loss, throughput performance, coverage probability analysis and outage probability performance. …”
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Tree-based contrast subspace mining method
Published 2020“…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…The simulation results indicate that the algorithm is able to segregate and assign the tasks for each scanning head and also able to find the shortest scanning path for different types of objects coordination. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Since EC, like genetic algorithm, relies on randomness and probabilities, it is cumbersome when constraints are present in the search. …”
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Refinement of Tuned Mass Damper parameters on machine support structure using dynamic Cuckoo Search algorithm
Published 2025“…This study proposes the use of a dynamic Cuckoo Search (CS) algorithm, a nature-inspired optimization method, to enhance the accuracy of TMD parameters when external factors, such as excitation frequency or structural properties, change. …”
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Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa
Published 2017“…The more number of marbles, the higher the search accuracy. In future, traditional marble game can be applied with other search algorithm to optimize the solution…”
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2023“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. …”
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2023“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. …”
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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
Published 2006“…This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…A new mutation vector inspired by the two-opposite path (2-Opt) algorithm with adaptive mutation scalar (F ) and crossover rate (CR) control parameters were employed to enhance the exploration and exploitation phases of the proposed algorithm. …”
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Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria
Published 2021“…Having only one parameter control (i.e. the switch probability, pa) to choose from the global search (i.e. exploration) and local search (i.e. exploitation) is the main strength of FPA as compared to other meta-heuristic algorithms. …”
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Performance analysis of pair-wise error probability for 1/3 and 1/4 subcarrier mapping ICI-SC scheme in STFBC MIMO-OFDM system / Norhayati Abdullah
Published 2015“…The simulation results expressively show that the one third method subcarrier mapping technique with Decision Feedback Equalizer (DFE) and adaptive algorithm can provide the best system performance compared to the existing subcarrier mapping methods .The results shows that by using the one-third subcarrier mapping scheme with an adaptive algorithm Normalised Least Means Square (NLMS), an efficient bandwidth can be achieved, ICI and ISI effects can be reduced with 24% of improvement compared to one-third subcarrier mapping Recursive Least Square (RLS) DFE in the MIMO-OFDM system.…”
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Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria
Published 2021“…Having only one parameter control (i.e. the switch probability, pa) to choose from the global search (i.e. exploration) and local search (i.e. exploitation) is the main strength of FPA as compared to other meta-heuristic algorithms. …”
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