Hybrid precoding method for millimeter-wave massive MIMO systems based on IAFS algorithm by Haoyi CHEN, Guangqiu LI, Hui LI

“…The millimeter-wave massive multiple-input multiple-output (MIMO) systems can overcome the adverse effects of the free-space signal path loss through the partial connection hybrid precoding method, which has the advantages of low hardware complexity and high energy efficiency.When the number of input data streams is equal to the number of radio frequency (RF) links, the hybrid precoding method based on partially connected structure and serial interference cancellation can be used.When the number of input data streams is not equal to the number of RF links, a hybrid precoding method based on improved artificial fish swarm (IAFS) algorithm was proposed.The core idea is that based on the spectral efficiency optimization criteria and the characteristics of partial connected structure, the spectral efficiency optimization problem of analog recoding matrix variables was transformed into the spectral efficiency optimization problem based on vector variables, and then the IAFS algorithm was used to solve the spectrum efficiency optimization problem.The simulation results show that the proposed method has good spectral efficiency and energy efficiency under the condition of low signal-to-noise ratio, and is expected to be applied in the real scene.…”
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Hybridization of deep learning models with crested porcupine optimizer algorithm-based cybersecurity detection on industrial IoT for smart city environments by Sarah A. Alzakari, Mohammed Aljebreen, Mashael M. Asiri, Wahida MANSOURI, Sultan Alahmari, Mohammed Alqahtani, Shaymaa Sorour, Wafi Bedewi

“…To accomplish that, the CCPOA-HDLM method comprises distinct processes such as min-max normalization, improved Salp swarm algorithm (ISSA)-based feature selection, Multi-Channel Convolutional Neural Network - Recurrent Neural Network (MCNN-RNN)-based cybersecurity detection, and crested porcupine optimizer (CPO)-based parameter selection process. …”
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A Robust Salp Swarm Algorithm for Photovoltaic Maximum Power Point Tracking Under Partial Shading Conditions by Boyan Huang, Kai Song, Shulin Jiang, Zhenqing Zhao, Zhiqiang Zhang, Cong Li, Jiawen Sun

“…To address these challenges, this paper introduces a hybrid algorithm that integrates an improved salp swarm algorithm (SSA) with the perturb and observe (P&O) method. …”
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Reducing PAPR in NOMA Waveforms Using Genetic-Enhanced PTS and SLM: A Low-Complexity Approach for Improved throughput, power spectral density, and Power Efficiency by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…To overcome these issues, this paper introduces new Particle Swarm Optimization (PSO)-improved partial transmit sequence (PTS) and Selective Mapping (SLM) schemes that optimally choose phase factors with much lower search complexity. …”
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Design and Analysis of a Hybrid MPPT Method for PV Systems Under Partial Shading Conditions by Oğuzhan Timur, Bayram Kaan Uzundağ

“…In this study, a novel hybrid MPPT method based on Perturb & Observe and Particle Swarm Optimization that mainly aims to determine global operating point, is proposed. …”
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The Application of Compound Control Algorithm in Photovoltaic System MPPT by WANG Shenghui, LI Yilun, ZHENG Hong, GAO Shan

“…Aiming at the problem that the output array exhibits multipeak characteristics when the PV array is partially shaded or unevenly illuminated, the traditional singlepeak MPPT algorithm is difficult to track the maximum power point A hybrid algorithm is proposed to improve the particle swarm combined with the sliding mode search Firstly, the probability judgment criterion of improved simulated annealing algorithm is introduced into the standard particle swarm optimization algorithm; the law of inertia weight change is improved; the disturbance parameter is added to the learning factor Secondly, using the sliding mode extreme value search algorithm, the suspected optimal value obtained by the particle swarm optimization algorithm is continuously optimized, and finally the maximum power point is found The simulation results show that the composite control algorithm can track the maximum power point quickly and accurately under different shadow conditions, and avoid the system falling into the local optimum value…”
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Integrated DDPG-PSO energy management systems for enhanced battery cycling and efficient grid utilization by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Wen Yao Low, Nor Zaihar Yahaya, Ahmed Tijjani Dahiru, Temitope Ibrahim Amosa, Shehu Lukman Ayinla

“…This study integrates Deep Deterministic Policy Gradient (DDPG) with Particle Swarm Optimization (PSO) to enhance exploration and exploitation in the optimization process, aiming to improve energy resource utilization and reduce costs in hybrid energy systems. …”
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K-Nearest Neighbors hybrid method for maximum power point tracking under partial shading for photovoltaic power systems by Djamel Guessoum, Maen Takrouri, Mohammad Rabih, Maissa Farhat, Sufian A. Badawi

“…This paper presents a hybrid approach that integrates the K-Nearest Neighbors (KNN) machine learning algorithm with an enhanced local search for optimizing the duty cycle D. …”
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Hybrid Sensor Placement Framework Using Criterion-Guided Candidate Selection and Optimization by Se-Hee Kim, JungHyun Kyung, Jae-Hyoung An, Hee-Chang Eun

“…This study presents a hybrid sensor placement methodology that combines criterion-based candidate selection with advanced optimization algorithms. …”
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Machine learning prediction and explainability analysis of high strength glass powder concrete using SHAP PDP and ICE by Muhammad Sarmad Mahmood, Tariq Ali, Inamullah Inam, Muhammad Zeeshan Qureshi, Syed Salman Ahmad Zaidi, Muwaffaq Alqurashi, Hawreen Ahmed, Muhammad Adnan, Abdul Hakim Hotak

“…To further enhance performance, XGB was optimized using Particle Swarm Optimization (PSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO). …”
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Hardware-in-loop implementation of an adaptive MPPT controlled PV-assisted EV charging system with vehicle-to-grid integration by Surabhi Singh, Hari Om Bansal

“…This paper developed and compared perturb and observe (P&O), Particle swarm optimization (PSO), and hybrid PSO + Adaptive neuro-fuzzy inference system (ANFIS) based algorithm for MPPT. …”
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Optimized physics-informed neural networks for deciphering of external source pollutants in a swirling flow induced by a constant torsional motion by Shridhar M, Umair Khan, Rahul Makwana, Ankur Kulshreshta, N.B. Naduvinamani

“…The flow, heat and mass transport attributes are assessed using the Physics-informed neural network (PINN). This model is optimized by a hybrid genetic algorithm and particle swarm optimization to address the flow, heat and mass transport attributes via neural networks. …”
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A Novel PAPR in OTFS Systems Through ISSA-PTS and ISPR Techniques by Gerges Mansour Salama, Amira A. Mohamed, Aziza I. Hussein, M. Mourad Mabrook

“…This study introduces two novel PAPR reduction techniques: a hybrid approach combining the Improved Salp Swarm Algorithm (ISSA) with Partial Transmit Sequence (PTS) and an innovative Iterative Sub-block Phase Rotation (ISPR) method. …”
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Predicting the Traffic Crashes of Taxi Drivers by Applying the Non-Linear Learning of ANFIS-PSO with M5 Model Tree by E. Abbasi, M. Hadji Hosseinlou

“…A novel technique is been developed by applying nonlinear-learning of composition model of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Particle Swarm Optimization (PSO) with M5 model tree. In order to improve the generalization ability of a single data driving algorithm, a cluster of ANFIS models with different nodes and hidden layers are implemented to extract the inherent relationship between traffic accident rates and human factors. …”
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