Search Results - (( time optimization method algorithm ) OR ( using action method algorithm ))*

Harris Hawk Optimization-Based Deep Neural Networks Architecture for Optimal Bidding in the Electricity Market by Kavita Jain, Muhammed Basheer Jasser, Muzaffar Hamzah, Akash Saxena, Ali Wagdy Mohamed

“…In this research, we provide HHO-NN (Harris Hawk Optimization-Neural network), a novel algorithm based on Harris Hawk Optimization (HHO) that is capable of fast convergence when compared to previous evolutionary algorithms for automatically searching for meaningful multilayered perceptron neural networks (MPNNs) topologies for optimal bidding. …”
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Evaluation of energy-saving potential for optimal time response of HVAC control system in smart buildings by Homod R.Z., Gaeid K.S., Dawood S.M., Hatami A., Sahari K.S.

“…Controllers; Delay control systems; Energy efficiency; Gradient methods; Intelligent buildings; Membership functions; Optimal systems; Optimization; Response time (computer systems); Semiconductor device manufacture; Thermal comfort; Water craft; Cluster adaptive training; Energy efficient building; Energy saving potential; Fuzzy membership function; Manufacturing industries; Nelder-Mead simplex search; Semiconductor manufacturing process; Temperature and humidities; HVAC; algorithm; building; control system; electronic equipment; energy conservation; manufacturing; residential energy; temporal analysis…”

A simplified adaptive neuro-fuzzy inference system (ANFIS) controller trained by genetic algorithm to control nonlinear multi-input multi-output systems by Lutfy, Omar F., Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce

“…A real-coded genetic algorithm (GA) was utilized to optimize the premise and the consequent parameters of the ANFIS controller, instead of the hybrid learning methods that are widely used in the literature. …”
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Modular motor driver with torque control for gripping mechanism by How D.N.T., Baharuddin M.Z., Mohideen S.S.K., Sahari K.S.M., Anuar A.

“…These graphical outputs of the controller was evaluated based on the response time, degree of overshooting, and steady-state error to determine the most optimal method of control to be implemented in torque control scheme. …”

Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System by Arab, Ali

“…It plays the role of objective function of the maintenance scheduling optimization problem. Using a production related heuristic method which is called system value method, the value of each workstation is determined. …”
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A conceptual framework for multi-objective optimization of building performance: Integrating intelligent algorithms, simulation tools, and climate adaptation by Rong, Li, Shari, Zalina, Ab Kadir, Mohd Zainal Abidin

“…A thematic analysis of 40 peer-reviewed articles was conducted using ATLAS.ti, revealing three dominant research themes: intelligent algorithms, building performance simulation techniques, and adaptive design for climate change. …”
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A simplified PID-like ANFIS controller trained by genetic algorithm to control nonlinear systems by Lutfy, Omar Farouq, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Abbas, Kassim A.

“…Moreover, the GA was used to find the optimal settings for the input and output scaling factors for this controller, instead of the widely used trial and error method. …”
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Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

Study on tourism development using CRITIC method for tourist satisfaction by Yang, Xi, Ali, Noor Azman, Hon Tat, Huam

“…This paper presents a novel approach for evaluating tourist satisfaction and developing optimized strategies by integrating the CRITIC method, deep learning with Multilayer Perceptron (MLP), and Genetic Algorithms (GA). …”
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Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

“…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
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Optimized type 2 fuzzy logic control for low-speed vehicle pedal pressing automation using hybrid spiral sine cosine algorithm by Azrul Azim, Abdullah Hashim, Nor Maniha, Abdul Ghani, Salmiah, Ahmad, Mohd Ruzaini, Hashim, Noor Zirwatul Ahlam, Naharuddin, Addie, Irawan

“…The research investigates two FLC approaches: the standard Type 1 FLC and the advanced Type 2 FLC, both optimized using the Hybrid Spiral Sine Cosine Algorithm (SSCA). …”
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Modeling sub-event dynamics in first-person action recognition by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal S.

“…We propose a method to represent the high level dynamics of sub-events in first-person videos by dynamically pooling features of sub-intervals of time series using a temporal feature pooling function. …”
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Existence and uniqueness for the evolutionary impulse control problem using an asynchronous algorithms by Haiour M., Bencheikh Le Hocine M.E.A., Jan R., Himadan A., Boulaaras S.

“…This methodology integrates semi-implicit techniques with respect to the variable t and employs spatial approximation via finite element methods. We establish a pivotal connection between a fixed-point mapping and the discrete EQVIs system, utilizing it to formulate a discrete algorithm featuring a semi-implicit time scheme. …”

Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm by Abd Rahman, Mohd Shahrizan, Jamaludin, Nor Azliana Akmal, Zainol, Zuraini, Tengku Sembok, Tengku Mohd

“…The findings of this study have significant implications for National Oil Companies (NOCs) and operators, facilitating proactive intervention strategies, enhancing transparency in decision-making, and supporting the early monetization of resources. Ultimately, this method improves the protection of project schedules, optimizes infrastructure utilization, and maximizes economic returns and strategic alignment in Malaysia's energy industry.…”
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Hierarchical extreme learning machine based reinforcement learning for goal localization by AlDahoul, Nouar, Htike, Zaw Zaw, Akmeliawati, Rini

“…In this paper, reinforcement learning (RL) method was utilized to find optimal series of actions to localize the goal region. …”
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Design of field programmable gate array-based proportional-integral-derivative fuzzy logic controller with tunable ganin by Obaid, Zeyad Assi

“…This block involves a tuning via scaling the universe of discourse and is able to accept optimal scaling gains. The particle swarm optimization method (PSO) is used to obtain the optimal values of these gains. …”
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Graphical user interface test case generation for android apps using Q-learning / Husam N. S. Yasin by Husam , N. S. Yasin

“…Instead of randomly selecting the inputs, the test generator learns how to act in an optimal way that explores new states by using new actions to gain more rewards. …”
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A hybrid simple exponential smoothing-barnacles mating optimization approach for parameter estimation: Enhancing COVID-19 forecasting in Malaysia by Azlan, Abdul Aziz, Zuriani, Mustaffa, Suzilah, Ismail, Nor Azriani, Mohamad Nor, Nurin Qistina, Mohamad Fozi

“…Therefore, this study aims to propose a new hybrid model, the Single Exponential Smoothing (SES)-Barnacles Mating Optimization (BMO) algorithm, to estimate the optimal smoothing parameter alpha and initial value that can improve the percentage of forecast accuracy. …”
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A genetically trained simplified ANFIS controller to control nonlinear MIMO systems by Lutfy, Omar F., Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce

“…In addition, the real-coded genetic algorithm (GA) has been utilized to train this MIMO ANFIS controller, instead of the hybrid learning methods that are widely used in the literature. …”
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Enhanced PID for pedal vehicle force control using hybrid spiral sine-cosine optimization and experimental validation by Azrul Azim, Abdullah Hashim, Nor Maniha, Abdul Ghani, Mohammad Osman, Tokhi

“…This study develops and validates a force feedback control system for automotive pedals utilizing an optimized PID controller using the hybrid Spiral Sine-Cosine algorithm (SSCA). …”
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