Search Results - (( variable extractions path algorithm ) OR ( its contribution function algorithm ))

March-based diagnosis algorithm for static random-access memory stuck-at faults and transition faults by Mat Isa, Masnita

“…March tests are widely used during functional testing due to its higher fault coverage and less time complexity. …”
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Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems by Mansor, Nur Farraliza

“…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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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…The performance of DE algorithm depends heavily on the selected mutation strategy and its associated control parameters. …”
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An empirical study of density and distribution functions for ant swarm optimized rough reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

“…To describe relative probability of different random variables, Probability Density Function (PDF) and the Cumulative Density Function (CDF) are capable to specify its own characterization of Gaussian distributions. …”
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Pashto language stemming algorithm by Aslamzai, Sebghatullah, Saidah Saad

“…Furthermore, the accuracy and strength of the proposed algorithm is evaluated using word count method. To validate the function of the developed algorithm, two native speakers of Pashto were recruited to evaluate the algorithm in terms of its accuracy and strength. …”
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An Innovative Signal Detection Algorithm in Facilitating the Cognitive Radio Functionality for Wireless Regional Area Network Using Singular Value Decomposition by Mohd. Hasbullah, Omar

“…This thesis introduces an innovative signal detector algorithm in facilitating the cognitive radio functionality for the new IEEE 802.22 Wireless Regional Area Networks (WRAN) standard. …”
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A review of the optimal allocation of distributed generation: Objectives, constraints, methods, and algorithms by Pesaran H.A M., Huy P.D., Ramachandaramurthy V.K.

Dynamic S-boxes and spiral permutation function on Fibonacci sequence for secure block cipher / Kamsiah Mohamed by Mohamed, Kamsiah

“…This is because the dynamic S-box would make it difficult for an attacker to recognise its elements. In this thesis, the Spiral Fibonacci is proposed for a permutation function to diffuse bit permutation in improving cryptography algorithm efficiency. …”
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A review of slicing techniques in software engineering by Shah, Asadullah, Raza, Ali, Hassan, Basri, Shah, Abdul Salam

“…A common practice now is to extract the sub models out of the giant models based upon the slicing criteria. …”
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A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts by Pratiwi, Lustiana, Choo, Yun Huoy, Draman @ Muda, Azah Kamilah

“…Coexistence, cooperation, and individual contribution to food searching by a particle (ant) as a swarm (ant) survival behavior, depict the common characteristics of both algorithms. …”
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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model by Ouwabunmi, Babalola AbdulHafeez

“…While the focus was on comparing standalone and hybrid models, the study identifies opportunities for future benchmarking against external tools to further validate its contributions. The findings contribute to both computational and biological research, offering insights into smORF prediction methodologies and their applications.…”
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

“…Thirdly, the thesis validates the algorithm's performance on standard constrained single objective and multi objective benchmark test functions. …”
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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia by Zaini, Farah Anishah, Sulaima, Mohamad Fani, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

“…However, the less optimal regularization parameter and the Gaussian kernel function in the LSSVM model have contributed to flawed forecasting accuracy and random generalization ability. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia by Sulaima, Mohamad Fani, Zaini, Farah Anishah, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

“…However, the less optimal regularization parameter and the Gaussian kernel function in the LSSVM model have contributed to flawed forecasting accuracy and random generalization ability. …”
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The impact of population size on knowledge acquisition in genetic algorithms paradigm: Finding solutions in the game of Sudoku by Abu Bakar, Nordin, Mahadzir, Muhammad Fadhil

“…Population size is an important component in genetic algorithms (GAs).The concept of population in GAs has contributed to a unique searching strategy which empower its search process through the massive volume of the data in a population.The purpose of this study is to see how the impact of population size on genetic algorithms in producing correct solution for a Sudoku puzzle.Sudoku is a Japanese number puzzle game that has become a worldwide phenomenon.The puzzle involves completing a grid of cells by assigning a single number to each cell.The numbers in a row or a column must consist of any one of the numbers from 1 to 9; no repetition is allowed.GA will be used to generate the correct solution of Sudoku puzzles.The mechanism to produce legal Sudoku grid will follow the requirements needed and meet all the constraints.A fitness function is designed to evaluate legal grids and GA will be tested for performance and time efficiency.The challenges lie on how GA will represent a Sudoku grid in the process and the effectiveness of its operators such as crossover and mutation.The results show how different population size can produce different solutions.The best performance is observed at 500 population size.The paper will conclude with an insight of this value and its significance to the knowledge acquisition in GA paradigm..…”
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Enhancing performance of global path planning for mobile robot through Alpha–Beta Guided Particle Swarm Optimization (ABGPSO) algorithm by Ahmad, Javed, Ab Wahab, Mohd Nadhir, Ramli, Ahmad, Misro, Md Yushalify, Ezza, Wan Zafira, Wan Hasan, Wan Zuha

“…Particle Swarm Optimization (PSO) is widely used due to its strong search capabilities, but its standard form suffers from slow convergence and local optima trapping, limiting its performance in complex environments. …”
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Implementation Of Algorithm For Vehicle Anti-Collision Alert System In FPGA by Jidin, Aiman Zakwan, Lim, Siau Li, Kadmin, Ahmad Fauzan

“…Furthermore, it also triggers an alert if the driver is breaching the safe distance from the vehicle ahead. This algorithm has been successfully implemented in Altera DE0 FPGA and its functionality was validated via hardware experimental tests.…”
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Forecasting particulate matter concentration using linear and non-linear approaches for air quality decision support by Abdullah S., Ismail M., Ahmed A.N., Abdullah A.M.

SVM modelling of agarwood oil quality grading using radial basis function (RBF) and sequential minimal optimization (SMO) learning algorithms by Muhammad Haziq Haikal, Hisham, Nurlaila, Ismail, Nor Azah, Mohd Ali, Saiful Nizam, Tajuddin, Mohd Nasir, Taib

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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

“…Software modifications necessitate regression testing to address defects and verify functionality. Regression test case prioritisation (TCP) is used to revalidate modified software, ensuring its quality before release on the digital market. …”
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