Search Results - (( simulation optimization learning algorithm ) OR ( data adaptation optimization algorithm ))

Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
Get full text
Get full text

Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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

“…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
Get full text
Get full text

Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA by Zahari, Taha, Farzad, Tahriri, Siti Zawiah, Md Dawal

“…Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. …”
Get full text
Get full text
Get full text

Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
Get full text
Get full text
Get full text

Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
Get full text
Get full text

Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

“…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
Get full text
Get full text

Precision agriculture for corn using reinforcement learning by Tan, Carlton

“…RACKY serves as a versatile interface, facilitating effortless retrieval of detailed corn plant state information based on precise fertilizer or irrigation inputs through its intuitive API endpoints. Beyond data access, RACKY incorporates a sophisticated reinforcement learning agent based on the Proximal Policy Optimization (PPO) algorithm within the SWATGym. …”
Get full text
Get full text

Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

“…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
Get full text
Get full text
Get full text

Precision agriculture for corn using reinforcement learning by Tan, Carlton

“…RACKY serves as a versatile interface, facilitating effortless retrieval of detailed corn plant state information based on precise fertilizer or irrigation inputs through its intuitive API endpoints. Beyond data access, RACKY incorporates a sophisticated reinforcement learning agent based on the Proximal Policy Optimization (PPO) algorithm within the SWATGym. …”
Get full text
Get full text

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

Get full text
Get full text
Get full text
Get full text

Box-jenkins and genetic algorithm hybrid model for electricity forecasting system by Mahpol, Khairil Asmani

“…By adopting the GA blind search, the algorithm combines searching techniques and their capabilities to learn about the relationship of the pattern-recognition of the past data. …”
Get full text
Get full text

Adaptive Mechanism for GA-NN to Enhance Prediction Model by Faridah Sh Ismail, Nordin Abu Bakar, (UniKL MIIT)

“…In order to avoid result from local optimum scenario, GA optimizes synaptic weights of the network towards reducing prediction error. …”

Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

“…Also, the proposed algorithms focus on the need for cooperative learning that maintains the quality of service, adapts to the network dynamics and achieves energy efficiency in dense small-cell networks. …”
Get full text
Get full text

EDITORIAL: INTEGRATION OF HYDROLOGICAL MODELS AND MACHINE LEARNING TECHNIQUES FOR WATER RESOURCES MANAGEMENT by Ren Jie, Chin, Sai Hin, Lai

“…Hybrid models integrating physical-based simulations with machine learning-driven corrections reduce uncertainties, enhance computational efficiency, and enable adaptive water management. …”
Get full text
Get full text
Get full text
Get full text

Performance optimization of the parabolic trough power plant using a dual-stage ensemble algorithm by Elfeky K.E., Hosny M., Mohammed A.G., Chu W., Khatwa S.A., Wang Q.

Energy-Efficient Federated Learning With Resource Allocation for Green IoT Edge Intelligence in B5G by SALH, ADEB, NGAH, RAZALI, Audah, Lukman, SOON KIM, KWANG, ALJALOUD, KHALED A., TALIB, HAIRUL NIZAM

“…The proposal efficiently optimized the computation frequency allocation and reduced energy consumption in IoT devices by solving the bandwidth optimization problem in closed form. …”
Get full text
Get full text

Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function by Tan, Min Keng

Get full text
Get full text
Get full text

Energy-efficient federated learning with resource allocation for green IoT edge intelligence in B5G by Ngah, Razali, Salh, Adeeb, Audah, Lukman, Abdullah, Qazwan, Kim, Kwang Soon, Al-Moliki, Yahya Mohammed Hameed, AlJaloud, Khaled A., Talib, Md Hairul Nizam

“…The proposal efficiently optimized the computation frequency allocation and reduced energy consumption in IoT devices by solving the bandwidth optimization problem in closed form. …”
Get full text
Get full text
Get full text