Selection Hyper-heuristics for Population-based Meta-heuristics in Continuous Dynamic Environments

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Model-based estimation and control of wheel slip in locomotives

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Energy-water management and minimal cost solution in residences

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Fluid-Structure Interaction of NREL 5-MW Wind Turbine by Abd-Elhay, Mohamed Sayed Elkady

“…This study introduced two passive optimization methods: material Bend Twist Coupling (BTC) and blade root fixation. …”
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Reliable Outdoor Ai-Based Autonomous Uav Localization and Trajectory Tracking Using Cellular Networks by Afifi, Ghada

“…We utilize conventional optimization methods to determine the optimal bound of the solution of the reliable UAV navigation problem. …”
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Deep Reinforcement Learning-Based Approaches for the MPPT Control of Standalone Solar PV Systems by Nwachukwu, Sampson

“…Recently, metaheuristic optimization algorithms, including particle swarm optimization (PSO), genetic algorithm (GA), etc., have been used to deal with the limitations of classical methods. …”
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Reinforcement learning for power scheduling in a grid-tied pv-battery electric vehicles charging station by Arwa, Erick Odhiambo

“…Unlike other optimization methods such as numerical and soft computing techniques, RL does not require an accurate model of the optimization environment in order to arrive at an optimal solution. …”
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The role and production of traditional leafy vegetables in three rural communities in South Africa

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Multi-purpose applications of energy storage systems in a power system network by Okafor, Chukwuemeka Emmanuel

“…When comparing the proposed optimal sizing approach with existing methods, the suggested methodology performed better due to its ability to eliminate the weighting factors, thereby ensuring that none of the objective functions dominate the other. …”
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Predictive Maintenance: Leveraging Hybrid LSTM-CNN Architectures for Enhanced Performance by El Sadeek, Kamal Mohamed

“…These findings pave the way for future research that incorporates real-time streaming data, explores more advanced architectures such as Transformers, and investigates domain adaptation methods to bridge the gap between simulated and real-world applications.…”
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A mixed integer linear programming model for truck-shovel scheduling to minimize fuel consumption

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Maximum likelihood estimation for Cox regression under risk set sampling

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Efficient energy management in ultra-dense wireless networks by Wambi, Paul James

“…Finally, the statistical and mathematical results generated through the simulations indicate that the proposed scheme is the closest in NEE performance to the Exhaustive Search algorithm, and hence superior to the other sub-optimal algorithms it is compared to.…”
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Damping of electromechanical oscillations using power system stabilizers by Ahmed, Shaheen Sooleman

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Time Sensitive Networking for Wi-Fi Based Wireless Industrial Environments by Kinabo, Arnold Baraka Doste

“…The prototype model runs in a simulation environment, and was developed using methods that involved reusing and modifying the present wireless architecture to support the TSN traffic. …”
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Discrete element modeling of a vibratory subsoiler by Van der Linde, Jaco

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Youth ministry and community development : a practical-theological perspective

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The role of Egypt's industrial policy in SMEs empowerment: A focus on industrial land allocation and licensing by Elkhishin, Dina

“…The study analyzes the current situation of industrial licensing and land allocation frameworks and how they are facilitating the inclusion of SMEs in the industrial market. …”
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Energy efficiency control of direct expansion air conditioning systems

“…To realize this objective and to consider the interaction effects between rooms, we present an autonomous hierarchical distributed control (AHDC) method. The upper level is an open loop nonlinear optimizer, which only collects measurement information and solves a distributed steady state optimization problem to adaptively and automatically generate time-varying and optimised reference points of indoor CO2 concentration, relative humidity and air temperature for the lower-layer controllers, by minimizing the demand and energy costs of a multi-zone building ME A/C system under the TOU price structure of electricity according to the changing circumstance during the day. …”
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