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1
Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems
Published 2018“…Therefore,it is of great interest that we find adjustments for these parameters in this research.There are two contributions to this research.The first one is having HMCR parameter using step function and the linear increase function while the second is applying the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter.There are three proposed models on the alteration of HMCR parameters based on the use of the fundamental step function;namely,the constant interval of step function, and its dynamic increase and decrease interval functions.The experimental results revealed that our proposed approach is superior to other state of the art harmony searches either in specific or generic cases. …”
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2
An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…Although useful, the existing algorithms does not provide any comparative data to select an algorithm based on the problem size and difficulty and the use of other neighborhood algorithms (including Great Deluge and Late Acceptance Hill Climbing) has not been sufficiently explored as well. …”
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3
Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions
Published 2014“…Owing to the fact that they are new and much of their relative performance are still unknown (as compared to other established meta-heuristic algorithms), Bacterial Foraging Optimization Algorithm (BFO) and Bat Algorithm (BA) have been adopted for comparison using the 12 selected benchmark functions. …”
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4
Hybrid harmony search algorithm for continuous optimization problems
Published 2020“…Addressing these aforementioned issues, this thesis proposes to augment HS with adaptive tuning using Grey Wolf Optimizer (GWO). Meanwhile, to enhance its exploitation, this thesis also proposes to adopt a new variant of the opposition-based learning technique (OBL). …”
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5
Enhancing CI engine performance and emission control using a hybrid RSM–Rao algorithm for ZnO-doped castor–neem biodiesel blends
Published 2025“…This involves the impact of input engine variable ranges such as fuel blends (10–40 v/v%), ZnO dosage (20–100 ppm). engine speed (800–2000 rpm), and engine load (10–40 %) on performance indices (PI) such as brake power (BP), and brake thermal efficiency (BTE) and emission attributes (EAs) namely carbon monoxide (CO), unburnt hydrocarbon (UHC), oxide of nitrogen (NOx) as responses. RSM was used to plan the design of the experiment and detect the optimal engine conditions for enhancing PI and reducing EAs while 3 algorithms were used to solve a multi-objective function. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Fuzzy Type-1 Triangular Membership Function Approximation Using Fuzzy C-Means
Published 2020“…This research focuses on generating the parametric values of the triangular membership function using a novel method. Initially, the Fuzzy C-means algorithm is utilized to generate the parameters values of the Gaussian membership function. …”
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Fast sequential learning methods on RBF-network using decomposed training algorithms
Published 2004“…This work investigates novel sequential learning methods applied on a decomposed form of training algorithms using radial basis function (RBF) network. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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An Arithmetic-Trigonometric Optimization Algorithm with Application for Control of Real-Time Pressure Process Plant
Published 2022“…This paper proposes a novel hybrid arithmeticâ��trigonometric optimization algorithm (ATOA) using different trigonometric functions for complex and continuously evolving real-time problems. …”
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Effect of fitness function on localization performance in range-free localization algorithm
Published 2024“…However, so far there is no literature to investigate the effect of fitness function on rang-free localization algorithm. Firstly, this study comprehensively reviews and classifies the frequently-used localization fitness function in range-free localization scheme. …”
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Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column
Published 2005“…In particular, two dimensional fuzzy number concept and the pyramidal membership functions were adopted along with the use of a triangular plane as the induced output parameter. …”
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13
Using genetic algorithms as image watermarking performance optimizer / Zuhaili Zahid
Published 2008“…The process of embedding and retracting the data cause the original embedded data to be distorted as a side effect of the current method used. Due to the frequently use of rounding approach, embedded data or watermark hidden in an image is retrieved differently from the original watermark (Shih et al, 2004). …”
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14
Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization
Published 2022“…In the case of highly dispersive and nonlinear channels, it is well known that neural network-based equalizers are more effective than linear equalizers, which use finite impulse response filters. An alternative approach to training neural network-based equalizers is to use metaheuristic algorithms. …”
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Hybrid subjective evaluation of rule Exraction Algorithm using Weighted Subsethood-Based (WSBA)
Published 2013“…Fuzzy rules are important elements that being highlighted in any fuzzy expert system.This research proposes the framework of subjective performance evaluation using fuzzy technique for ranking the performance of the financial performance of a company under a multi criteria environment.There are a lot of techniques used such as fuzzy similarity function, fuzzy synthetic decision and satisfaction function have been adopted.The framework is based on fuzzy multi-criteria decision-making that consists of fuzzy rules.The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
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16
A multi-objective Spiral Dynamic algorithm and its application for PD design
Published 2017“…On the other hand, NS is a fast strategy to develop good Pareto Front (PF) characteristics for MO type algorithm. The proposed algorithm is tested with various benchmark functions used to test a newly developed MO algorithm. …”
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Enhancing three variants of harmony search algorithm for continuous optimization problems
Published 2021“…A convergence rate graph is also used to show the overall performance of the new algorithms.…”
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Hybrid subjective evaluation method using weighted subsethood - based (WSBA) rule generation algorithm
Published 2013“…Fuzzy rules are important elements that should take into account in any fuzzy expert system.This paper proposes the framework of subjective performance evaluation using fuzzy technique for ranking the attributes of different types of datasets under a multi-criteria environment.The techniques such as fuzzy similarity function, fuzzy synthetic decision and satisfaction function have been adopted in these fuzzy evaluation methods.The framework is based on fuzzy multicriteria decision-making that consists of fuzzy rules. …”
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Predictive modelling of machining parameters of S45C mild steel
Published 2016“…The PSO1 algorithm which used first main temperature objective function gives the best roughness value (0.52 μm) compared with other algorithms, followed by the AIS2 and PSO2 that give (0.86 μm). …”
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