A Hybrid Machine Learning Model for Accurate Autism Diagnosis by Durga Prasad Kavadi, Venkata Rami Reddy Chirra, Palacharla Ravi Kumar, Sai Babu Veesam, Sagar Yeruva, Lalitha Kumari Pappala

“…The proposed model employs an improved Squirrel Search Algorithm-based Feature Selection (ISSA-FS) to identify the most relevant features from medical data. …”
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Design of a Novel Fractional Whale Optimization-Enhanced Support Vector Regression (FWOA-SVR) Model for Accurate Solar Energy Forecasting by Abdul Wadood, Hani Albalawi, Aadel Mohammed Alatwi, Hafeez Anwar, Tariq Ali

“…This study presents a novel Fractional Whale Optimization Algorithm-Enhanced Support Vector Regression (FWOA-SVR) framework for solar energy forecasting, addressing the limitations of traditional SVR in modeling complex relationships within data. …”
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Optimization mechanism of attack and defense strategy in honeypot game with evidence for deception by Lihua SONG, Yangyang JIANG, Changyou XING, Guomin ZHANG

“…Using game theory to optimize honeypot behavior is an important method in improving defender’s trapping ability.Existing work tends to use over simplified action spaces and consider isolated game stages.A game model named HoneyED with expanded action spaces and covering comprehensively the whole interaction process between a honeypot and its adversary was proposed.The model was focused on the change in the attacker’s beliefs about its opponent’s real identity.A pure-strategy-equilibrium involving belief was established for the model by theoretical analysis.Then, based on the idea of deep counterfactual regret minimization (Deep-CFR), an optimization algorithm was designed to find an approximate hybrid-strategy-equilibrium.Agents for both sides following hybrid strategies from the approximate equilibrium were obtained.Theoretical and experimental results show that the attacker should quit the game when its belief reaches a certain threshold for maximizing its payoff.But the defender’s strategy is able to maximize the honeypot’s profit by reducing the attacker’s belief to extend its stay as long as possible and by selecting the most suitable response to attackers with different deception recognition abilities.…”
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Bayesian Optimization of insect trap distribution for pest monitoring efficiency in agroecosystems by Eric Yanchenko, Thomas M. Chappell, Anders S. Huseth

“…Insect trap networks targeting agricultural pests are commonplace but seldom optimized to improve precision or efficiency. Trap site selection is often driven by user convenience or predetermined trap densities relative to sensitive host crop abundance in the landscape. …”
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Short-Term Photovoltaic Power Forecasting Based on the VMD-IDBO-DHKELM Model by Shengli Wang, Xiaolong Guo, Tianle Sun, Lihui Xu, Jinfeng Zhu, Zhicai Li, Jinjiang Zhang

“…The model’s hyperparameters are optimized using the IDBO. …”
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Fault diagnosis of HVCB via the subtraction average based optimizer algorithm optimized multi channel CNN-SABO-SVM network by Qingjun Song, Jiuxin Wang, Qinghui Song, Kai Li, Wenchao Hao, Haiyan Jiang

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Load demand forecasting in air conditioning a rotor Hopfield neural network approach optimized by a new optimization algorithm by Mingguang Liu, Weibo Zhao, Ying Zhou, Mahdiyeh Eslami

“…The results showcase optimal performance, yielding an R2 value of 0.95, along with the lowest MSE, RMSE, and MAE values when compared to the other tested models. …”
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An Improved Particle Swarm Optimization for Solving Bilevel Multiobjective Programming Problem by Tao Zhang, Tiesong Hu, Yue Zheng, Xuning Guo

“…An improved particle swarm optimization (PSO) algorithm is proposed for solving bilevel multiobjective programming problem (BLMPP). …”
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Bio-inspired swarm intelligence for enhanced real-time aerial tracking: integrating whale optimization and grey wolf optimizer algorithms by GaoFeng Han

“…Abstract To address the decline in real-time tracking performance of moving targets in multi-UAV systems caused by uneven search coverage and low cooperation efficiency, the WGWO (Whale-Grey Wolf Optimization) model is proposed. The UAV swarm optimizes its flight paths using the spiral predation strategy of the WOA (Whale Optimization Algorithm) while employing a Kalman filter to process sensor data. …”
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Shape optimization of non-uniform parametric piezoelectric energy harvester beam by Milad Hasani, Hossein Shahverdi

“…The model, validated through finite element method (FEM) simulations and experimental data, enables rapid analysis and optimization of PEHs. …”
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Enhancing cybersecurity via attribute reduction with deep learning model for false data injection attack recognition by Faheed A.F. Alrslani, Manal Abdullah Alohali, Mohammed Aljebreen, Hamed Alqahtani, Asma Alshuhail, Menwa Alshammeri, Wafa Sulaiman Almukadi

“…Furthermore, the performance of the IDBN model is improved by the Cetacean Optimization Algorithm (COA)-based hyperparameter tuning process. …”
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Deep recurrent neural network with fractional addax optimization algorithm for influenza virus host prediction by Shweta Ashish Koparde, Sonali Kothari, Sharad Adsure, Kapil Netaji Vhatkar, Vinod V. Kimbahune

“…. • Addresses the data imbalance and improves model generalization, the oversampling technique is applied for data augmentation.The prediction model employs a Deep Recurrent Neural Network (DRNN) optimized by Fractional Addax Optimization 34 Algorithm (FAOA), a hybrid of Addax Optimization Algorithm (AOA) and Fractional Concept (FC), designed to perform 35 influenza virus host prediction. …”
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Virtual Cluster Partitioning Method of Active Distribution Networks Using Quantum Particle Swarm Optimization and Sector Search by Wei Liu, Yifan Tong, Xinran Xing, Xi Chen, Bo Hu, Qian Sun, Yufei Wang, Huaxin Li, Huidong Guo

“…This model simplifies the search for node locations and improves the algorithm's convergence speed. …”
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Innovative Hybrid Algorithm for Solving Vehicle Routing Problem with Time Window by A.M. Rahimi, B. Yadegari, M. Aboutalebi Esfahani

“…Hybrid approaches combine multiple optimization techniques to improve the quality and efficiency of solutions. …”
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Optimizing concrete strength: How nanomaterials and AI redefine mix design by Dan Huang, Guangshuai Han, Ziyang Tang

“…XGB was identified as the most effective ML algorithm for predicting compressive strength among others in this study (R2=0.974). …”
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Optimization of Flight Scheduling in Urban Air Mobility Considering Spatiotemporal Uncertainties by Lingzhong Meng, Minggong Wu, Xiangxi Wen, Zhichong Zhou, Qingguo Tian

“…Additionally, the proposed phased artificial lemming algorithm (ALA) outperforms traditional optimization algorithms in terms of solution quality. …”
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An efficient metaheuristic optimization algorithm for optimal power extraction from PV systems under various weather and load-changing conditions by Md.Al Imran Fahim, Md.Salah Uddin Yusuf, Monira Islam, Munshi Jawad Ibne Azad

“…To address these challenges, a new algorithm called horse herd optimization (HHO) has been applied to the maximum power point tracking (MPPT) controller. …”
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Evaluating the Efficiency of Gray Wolf Optimization and Colonial Competition Algorithm in Load Balancing of Distributed Systems by Asghar Molaei-Yeznabad, Amirhossein Dehghani

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A Method for Predicting Coal-Mine Methane Outburst Volumes and Detecting Anomalies Based on a Fusion Model of Second-Order Decomposition and ETO-TSMixer by Qiangyu Zheng, Cunmiao Li, Bo Yang, Zhenguo Yan, Zhixin Qin

“…Variational mode decomposition (VMD) parameters are optimized via a novel exponential triangular optimization (ETO) algorithm to extract multi-scale features. …”
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Stability Evaluation Method for Rock Slope-Anchorage Systems Based on Genetic Algorithms and Discrete Element Analysis by Peng Xia, Bowen Zeng, Yiheng Pan

“…The findings indicate that (1) the proposed evaluation method effectively accounts for the interaction between the anchorage structure and the rock slope, ensuring accurate results; (2) the method leverages the discrete element numerical model to quantitatively assess deformation and stress distribution within the system; (3) the integration of genetic algorithms significantly enhances the efficiency of identifying the most representative numerical model, and thereby the efficiency of stability evaluation is improved; and (4) the evaluation framework is capable of performing dynamic analyses of the stability evolution throughout the entire operational lifecycle of the rock slope anchorage system.…”
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