Search Results - (( parameter simulation based algorithm ) OR ( parameter solution learning algorithm ))

A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

“…Apart from the traditional gradient descent-based approach, metaheuristic algorithms can also be used to determine these parameters. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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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. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. Monte-Carlo simulation is performed by propagating uncertainty to investigate the dominant parameters affecting simulated results. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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Self-organizing network technique for resource allocation and mobility management in LTE femtocell network / Labeeb Mohsin Abdullah by Abdullah, Labeeb Mohsin

“…The third experiment was conducted using Vienna LTE simulator to evaluate the performance of the proposed optimized handover mechanism and reducing redundant handover by applying the most appropriate self-learning handover parameters. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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RESERVOIR PERFORMANCE PREDICTION IN STEAM HUFF AND PUFF INJECTION USING PROXY MODELLING by MERDEKA, MOHAMMAD GALANG

“…Therefore, developing predictive proxy models using machine learning algorithms is a suitable solution to address this concern. …”
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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. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus by Kumar, A., Ridha, S., Ilyas, S.U., Dzulkarnain, I., Pratama, A.

“…The algorithms also explain the effect of geometric and rheological parameters on the fluid flow attributes. …”
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Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…A comparative analysis is conducted with other well-known algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Biogeography-Based Optimization (BBO), Teaching-Learning Based Optimization (TLBO), and Beluga Whale Optimization (BWO). …”
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Precision agriculture for corn using reinforcement learning by Tan, Carlton

“…Beyond data access, RACKY incorporates a sophisticated reinforcement learning agent based on the Proximal Policy Optimization (PPO) algorithm within the SWATGym. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

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Precision agriculture for corn using reinforcement learning by Tan, Carlton

“…Beyond data access, RACKY incorporates a sophisticated reinforcement learning agent based on the Proximal Policy Optimization (PPO) algorithm within the SWATGym. …”
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Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

“…In essence, a neural network is an attempt to mimic the extremely complex human brain system, which is building an artificial brain that is able to self-learn intelligently. On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. …”
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Mobility-aware Offloading Decision For Multi-access Edge Computing In 5g Networks by Saeid Jahandar, Lida Kouhalvandi, Ibraheem Shayea, Mustafa Ergen, Marwan Hadri Azmi, Hafizal Mohamad

Machine learning‐based approach for bandwidth and frequency prediction of circular SIW antenna by Alam, Md Mahabub, Nurhafizah, Abu Talip Yusof, Ahmad Afif, Mohd Faudzi, Tomal, Md Raihanul Islam, Haque, Md Ershadul, Rahman, Md. Suaibur

“…A predictive ML framework was developed using six regression algorithms trained on significant geometrical parameters, such as ring slot radius, via diameter, and feedline width. …”
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Self-Organizing Network technique for resource allocation and mobility management in LTE femtocell network / Labeeb Mohsin Abdullah by Abdullah, Labeeb Mohsin

“…The commonality between the aforementioned issues of concern is the adoption of Self- Organizing Network (SON) technology concept as the basis for the proposed solutions for the above-mentioned challenges. MATLAB and Vienna LTE simulators were used to conduct the experiments for the proposed algorithms, approaches and schemes and also used to verify the results……”
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