Search Results - (( parameter optimization strategy algorithm ) OR ( using selection process algorithm ))

Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems by Yasear, Shaymah Akram

“…This indicates the capability of the algorithm in exploring the search space. The 2S-ENDSHHMO algorithm can be used to improve the search process of other MOSI-based algorithms and can be applied to solve MOPs in applications such as structural design and signal processing.…”
Get full text
Get full text
Get full text
Get full text

A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
Get full text
Get full text

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

“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
Get full text
Get full text

Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
Get full text
Get full text

Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
Get full text
Get full text

Nature-inspired parameter controllers for ACO-based reactive search by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

“…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
Get full text
Get full text
Get full text

A comparative study for parameter selection in online auctions by Gan, Kim Soon

“…Hence, this work attempts to improve an existing bidding strategy by taking into accounts the evolution of various model of generic algorithm in optimizing the parameter of the bidding strategies. …”
Get full text
Get full text
Get full text

Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

“…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
Get full text
Get full text

Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection by Iqbal, Muhammad

“…Meta-heuristic algorithms have become popular in finding optimal solutions for nonlinear complex problems. …”
Get full text
Get full text
Get full text
Get full text

Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller by Ismail, H. Muh Yusuf

“…The performance of GA can be further improved by using different combinations of selection strategies, crossover and mutation methods, and other genetic parameters such as population size, probability of crossover and mutation rate. …”
Get full text
Get full text
Get full text
Get full text

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…Experimental results of the proposed strategy are compared with other advanced meta-heuristic algorithms using the Otsu and Kapur fitness functions. …”
Get full text
Get full text
Get full text

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…Experimental results of the proposed strategy are compared with other advanced meta-heuristic algorithms using the Otsu and Kapur fitness functions. …”
Get full text
Get full text
Get full text

Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…The ADAM optimizer effectively tackles challenges in continuous parameter optimization by dynamically updating the model's weights and biases, adapting the learning rate for each parameter based on accumulated historical gradient information to achieve more efficient minimization of the loss function during training. …”
Get full text
Get full text
Get full text

Investigation of cross-entropy-based streamflow forecasting through an efficient interpretable automated search process by Chong K.L., Huang Y.F., Koo C.H., Sherif M., Ahmed A.N., El-Shafie A.

“…Due to the distinctive characteristics of these two adopted forms, selecting the correct algorithm for the machine learning problem along with their hyperparameter tuning process is critical to the realization of the desired results. …”

Inertia weight strategies in GbLN-PSO for optimum solution by Nurul Izzatie Husna, Fauzi, Zalili, Musa

“…In the PSO algorithm, inertia weight is an important parameter to determine the searching ability of each particle. …”
Get full text
Get full text
Get full text
Get full text

Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

“…The AFW algorithm reduces unnecessary computations by focusing only on useful edge entries in the graph, thereby expediting the optimization process. …”
Get full text
Get full text
Get full text

Optimization of operating cost and energy consumption in a smart grid by Mahdi, Baqer Saleh, Sulaiman, Nasri, Shehab, Mohanad Abd, Shafie, Suhaidi, Hizam, Hashim, Mohd Hassan, Siti Lailatul

“…A decision-making process is implemented to select the optimal solution from the non-dominated alternatives. …”
Get full text
Get full text

Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…Three major problems are encountered when designing metaheuristics; the first problem is balancing exploration with exploitation capabilities (which leads to premature convergence or trapping in the local minima), while the second problem is the dependency of the algorithm on the controlling parameters, which are parameters with unknown optimal values. …”
Get full text
Get full text

Development of efficient t-way test data generation algorithm and execution strategies by Khandakar Fazley, Rabbi

“…In current practice, usually the test-data are selected and executed randomly. Many useful strategies (2-Way and TWay sampling) were developed to generate test-data and facilitate smooth testing process. …”
Get full text
Get full text

Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

“…The other one is the network training’s environment optimization that is done through hyperparameter optimization by selecting and fine-tuning high impact parameters which include Optimizer, Learning Rate and Dropout to reduce error rate (loss function). …”
Get full text
Get full text
Get full text
Get full text