بدائل البحث:
storage optimization » swarm optimization (توسيع البحث), global optimization (توسيع البحث), whale optimization (توسيع البحث)
policy optimization » capacity optimization (توسيع البحث)
storage optimization » swarm optimization (توسيع البحث), global optimization (توسيع البحث), whale optimization (توسيع البحث)
policy optimization » capacity optimization (توسيع البحث)
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Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling
منشور في 2022"…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …"
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43
Reinforcement Learning for Resilient Aerial-IRS Assisted Wireless Communications Networks in the Presence of Multiple Jammers
منشور في 2024"…Hence, we leverage the light-weight Deep Reinforcement Learning (DRL) technique called Deep Deterministic Policy Gradient (DDPG) to optimize trajectory and IRS phase shifts and achieve multiple objectives jointly. …"
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44
Defense against adversarial attacks: robust and efficient compressed optimized neural networks
منشور في 2024"…First, introducing a pioneering batch-cumulative approach, the exponential particle swarm optimization (ExPSO) algorithm was developed for meticulous parameter fine-tuning within each batch. …"
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45
Multi-Objective Optimization for Food Availability under Economic and Environmental Risk Constraints
منشور في 2024"…Deploying the Analytical Hierarchy Process (AHP), this study evaluates climate change risks associated with seven different suppliers for three key crops, considering a range of factors, including surface temperature, arable land, water stress, and adaptation policies. Utilizing these assessments, a multi-objective optimization model is developed and solved using MATLAB (R2018a)’s Genetic Algorithm, aiming to identify optimal suppliers to meet Qatar’s food demand, with consideration of the economic, environmental, and risk factors. …"
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46
Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review
منشور في 2023"…The ubiquitous DRL architecture, by learning from the dynamism inherent in PSs, produces near-optimal actions for PSS. This article provides a rigorous review of the latest research efforts focused on DRL to derive PSS policies while accounting for the unique properties of power grids. …"
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47
An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization
منشور في 2022"…First, an efficient feature selection algorithm based on particle swarm optimization (PSO) is proposed. …"
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48
AI-driven nonlinear optimization for knowledge extraction and pattern analysis in IoT-enabled data mining systems
منشور في 2025"…On smart grid, city traffic, and industrial data, a modular computing framework is constructed consisting of fog computing over edges, cloud storage and embedded AI engines. The result of the experiment is that nonlinear optimization algorithms are better than the classical linear and clustering algorithms in accuracy and effectiveness, which tells of the presence of multi-layered latent structures that are significant in the analytics of IoT. …"
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49
Integrated Energy Optimization and Stability Control Using Deep Reinforcement Learning for an All-Wheel-Drive Electric Vehicle
منشور في 2025"…To this end, three model-free DRL-based methods, based on deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and TD3 enhanced with curriculum learning (CL TD3), are developed for determining optimal yaw moment control and energy optimization online. …"
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50
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51
A comprehensive review of deep reinforcement learning applications from centralized power generation to modern energy internet frameworks
منشور في 2025"…We present a structured taxonomy covering value-based, policy-based, actor-critic, model-based, and advanced multi-agent and multi-objective approaches, and link algorithms to tasks such as dispatch, microgrid coordination, real-time pricing, load balancing, and demand–response. …"
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52
Effective dispatch strategies assortment according to the effect of the operation for an islanded hybrid microgrid
منشور في 2022"…The proposed off-grid microgrid's CO<sub>2 </sub>emissions, total net present cost (NPC), and the Levelized cost of energy (LCOE) have all been optimized. In HOMER software, all the possible dispatch algorithms were analyzed, and the power system responses and reliability study were carried out using DIgSILENT PowerFactory. …"
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53
A depth-controlled and energy-efficient routing protocol for underwater wireless sensor networks
منشور في 2022"…The proposed energy-efficient routing protocol is based on an enhanced genetic algorithm and data fusion technique. In the proposed energy-efficient routing protocol, an existing genetic algorithm is enhanced by adding an encoding strategy, a crossover procedure, and an improved mutation operation that helps determine the nodes. …"
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54
Adaptive temperature control of a reverse flow process by using reinforcement learning approach
منشور في 2024"…First, a policy iteration algorithm is introduced to learn the optimal solution of the associated linear-quadratic control problem online. …"
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55
Peak Loads Shaving in a Team of Cooperating Smart Buildings Powered Solar PV-Based Microgrids
منشور في 2021"…The main objective is to formulate a constrained optimization problem embedded in a model predictive control (MPC) scheme to optimally control the operation of each microgrid to reduce/shave the peak load in case of occurrence, optimizing the power flows exchanges and energy storages, while ensuring a high quality of service to the EVs owners in each microgrid. …"
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56
DRL-Based IRS-Assisted Secure Visible Light Communications
منشور في 2022"…The DDPG-based algorithm provides an optimized solution that can adapt to the large size of design parameters and act fast to the channel variations due to users’ mobility. …"
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57
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DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
منشور في 2024"…To address this complexity optimally, we propose a deep reinforcement learning (DRL) approach based on the deep deterministic policy gradient (DDPG) technique. …"
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59
Advanced Quantum Control with Ensemble Reinforcement Learning: A Case Study on the XY Spin Chain
منشور في 2025"…<p dir="ltr">This research presents an ensemble Reinforcement Learning (RL) approach that combines Deep Q-Network (DQN) and Proximal Policy Optimization (PPO) algorithms to tackle quantum control problems. …"
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60