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1
A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…This obviously appeared in several metrics of performance evaluation, such as accuracy of localization, node localization rate, and implementation time. Conclusion: The proposed algorithm that utilized NMM is more functional to enhance the precision of localization because of particular characteristics that are the flexible implementation of NMM and the free cost of using the RSSI technique.…”
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2
A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm
Published 2013“…This paper attempts to implement a stochastic optimization algorithm called Bat Algorithm in order to find optimal values of the intrinsic parameters. …”
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3
A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem
Published 2022“…This study proposes to implement Bat algorithm, a stochastic optimization technique, to determine the optimum intrinsic parameter values. …”
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4
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
5
Optimal path planning algorithm for swarm robots using bat algorithm with mutation (bam)
Published 2022“…The objective of this study is to propose Bat Algorithm with Mutation (BAM) for solving the problem of obstacle avoidance of mobile robots. …”
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Undergraduates Project Papers -
6
Application of adaptive bats sonar algorithm to minimise car side impact design
Published 2017“…This project was focusing on the modification of bats sonar algorithm (BSA) and renamed to adaptive bats sonar algorithm (ABSA) due to some limitations of previous algorithm. …”
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Undergraduates Project Papers -
7
HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION
Published 2023“…In this paper, we study the advantages of fusing the Meta-Heuristic Bat Algorithm with Heuristic Optimization. We have implemented the Meta- Heuristic Bat Algorithm and tested it on a heterogeneous swarm. …”
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8
Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions
Published 2014“…In order to help engineers make a sound decision on the selection amongst the best meta-heuristic algorithms for the problem at hand, there is a need to assess the performance of each algorithm against common case studies. …”
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9
Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli
Published 2017“…There are five general steps implemented to develop the prototype. From the testing conducted, it shows that Bat algorithm produced moderate performance towards gliomas grading and segmentation. …”
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Thesis -
10
A bat-inspired t-way strategy for mixed-strength test suite generation
Published 2017“…BTS is the first t-way strategy that adopts the Bat-inspired algorithm as its core implementation and adopts the Hamming distance as the final selection criteria to enhance the exploration of new solution. …”
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11
A Surrogate Assisted Quantum-Behaved Algorithm for Well Placement Optimization
Published 2022“…The proposed approach utilizes different metaheuristic optimization techniques such as the Quantum-inspired Particle Swarm Optimization and the Quantum-behaved Bat Algorithm in different implementation phases. …”
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12
A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function
Published 2018“…Quantum-inspired particle swarm optimization is implemented on a 6-unit system to solve many-objective EED problems, and at the same time, to show the effectiveness of QPSO in large systems, it is also implemented in a 26-unit power generation system for ED problem. …”
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13
A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function
Published 2018“…Quantum-inspired particle swarm optimization is implemented on a 6-unit system to solve many-objective EED problems, and at the same time, to show the effectiveness of QPSO in large systems, it is also implemented in a 26-unit power generation system for ED problem. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…Based on literature, stereo algorithm is already being implemented to solve the distance measurement problem. …”
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16
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…It is attained successfully by combining the mean in K-Means algorithm, minimum and maximum in K-Midranges algorithm and compute their average as mean cluster of Hybrid mean. …”
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17
Determining the preprocessing clustering algorithm in radial basis function neural network
Published 2008“…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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18
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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