Search Results - (( simulation optimization learning algorithm ) OR ( loading optimization approach algorithm ))

An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms by Akhtar, Shamim, Muhamad Zahim, Sujod, Rizvi, Syed Sajjad Hussain

“…In this research work, an exhaustive parametric and empirical comparative study is conducted on the SEIL dataset for the recommendation of the optimal machine learning algorithm. The simulation results established the findings that Bagged Trees, Fine Trees, and Medium Trees are, respectively, the best-, second-best-, and third-best-performing algorithms in terms of efficacy. …”
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Joint optimization of resources allocation for quality of service aware next-generation heterogeneous cellular networks / Hayder Faeq Rasool Alhashimi by Hayder Faeq Rasool , Alhashimi

“…Finally, a State-Action-Reward-State-Action (SARSA) algorithm, which is a reinforcement learning approach, is proposed to solve the power allocation optimization problem. …”
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Frequency stabilization in interconnected power system using bat and harmony search algorithm with coordinated controllers by K., Peddakapu, M. R., Mohamed, P., Srinivasarao, P.K, Leung

“…To enhance the outcome of the proposed 2DOF–TIDN controller, its gain parameters are optimized with the use of a newly designed hybrid bat algorithm-harmony search algorithm (hybrid BA–HSA) technique. …”
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Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach by Shabbir Ahmed, Omar, Syed Mohamed Ali, Jaffar, Aabid, Abdul, Hrairi, Meftah, Mohd Yatim, Norfazrina Hayati

“…Additionally, the machine learning models successfully predict the optimal critical buckling load under mechanical and thermal loading conditions. …”
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A simulation-metaheuristic approach for finding the optimal allocation of the battery energy storage system problem in distribution networks by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Mohd Mawardi, Saari, Mohd Shawal, Jadin

“…This study will use Teaching Learning-Based Optimization (TLBO) as the main optimizer for the problem simulation. …”
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Multi-objective algorithms for effective resource management in Edge-Fog-Cloud computing by Saif, Faten Ameen Mohammed

“…First, proposed the Non-dominated Particle Swarm Optimization (NPSO) algorithm for workload allocation to reduce transmission delay in edge-cloud computing and imbalance load degree in edge-fog computing. …”
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A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

“…Besides, the performance of the Renewable Energy (RE)-based system has to be enriched with regard to settling time, accuracy, speed, and efficiency. Hence, to optimize the cost of integrating RES‘s through newly developed maximum power point tracking (MPPT) based optimization method such as grasshopper optimization algorithm (GOA) has been introduced. …”
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Application of artificial neural network for voltage stability monitoring / Valerian Shem by Shem, Valerian

“…This system analyzes the concerned variables and shows the stabilized value for load power (L) as the output. To solve this problem, this simulation implements the Artificial Neural Network approach using both standard back-propagation technique and hybrid technique (standard backpropagation and genetic algorithm (GA)). …”
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Machine Learning-Enabled Communication Approach for the Internet of Medical Things by Rahim Khan, Abdullah Ghani, Samia Allaoua Chelloug, Mohammed Amin, Aamir Saeed, Jason Teo

“…Furthermore, the machine learning approach helps enable these devices to update their routing tables simultaneously, and an optimal path could be replaced if a better one is available. …”
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Reinforcement learning-driven hybrid precopy/postcopy VM migration for energy-efficient data centers by Hidayat, Taufik, Ramli, Kalamullah, Harwahyu, Ruki, Salman, Muhammad, Gunawan, Teddy Surya

“…The data center state and the resource load, including the CPU, memory, and network, are represented in the agent’s state space using a two-layer graph neural network (GNN), and the asynchronous advantage actor–critic (A3C) algorithm is employed to dynamically determine whether to continue the precopy phase or switch to postcopy and optimize the trade-off among the total migration time, downtime, and energy consumption while adhering to the service-level agreement (SLA) constraints. …”
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Opposition-based learning simulated kalman filter for Numerical optimization problems by Mohd Falfazli, Mat Jusof

“…Simulated Kalman Filter (SKF) optimization algorithm is a population-based optimizer operated mainly based on Kalman filtering. …”
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Lightweight ontology architecture for QoS aware service discovery and semantic CoAP data management in heterogeneous IoT environment by Sukhavasi, Suman, Perumal, Thinagaran, Mustapha, Norwati, Yaakob, Razali

“…However, as the number of service requests grows, existing approaches suffer from increased discovery time and degraded Quality of Service (QoS). …”
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Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

“…These DRL-based algorithms optimize the local and global maximum power point (MPP) using deep Q-learning and deep deterministic policy gradient (DDPG). …”

Modeling and optimization of cold extrusion process by using response surface methodology and metaheuristic approaches by Ong, Pauline, Vui, Desmond Daniel Sheng Chin, Choon, Sin Ho, Chuan, Huat Ng

“…Subsequently, the analytical approach and metaheuristic algorithms, specifically the particle swarm optimization, cuckoo search algorithm (CSA) and flower pollination algorithm, were applied to optimize the extrusion process parameters. …”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct... by Wong Ling Ai

“…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”

Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms by Almubaidin M.A., Ahmed A.N., Sidek L.M., AL-Assifeh K.A.H., El-Shafie A.

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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

“…In the first proposed algorithm, SA is used to optimize the rule's discovery activity by an ant. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

“…The hybrid model is a novel approach for estimating sediment load based on various input variables. …”

Optimal under voltage load shedding based on stability index by using artificial neural network by Sharman, Sundarajoo

“…Nevertheless, to obtain the lowest amount to be shed in order to avoid voltage instability, optimization is required. An algorithm was developed to shed the optimal load by considering the load priority whereby the load with least priority will be shed first. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

“…From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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