Early detection of monkeypox: Analysis and optimization of pretrained deep learning models using the Sparrow Search Algorithm by Amna Bamaqa, Waleed M. Bahgat, Yousry AbdulAzeem, Hossam Magdy Balaha, Mahmoud Badawy, Mostafa A. Elhosseini

“…The novelty lies in using SpaSA to optimize pre-trained CNNs' performance. The Xception model achieves 97.66% accuracy without optimization. …”
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Optimizing Vehicle Body Cross-Sections Using a Parametric Mathematical Model by Zhaohui Hu, Shuai Mo, Huang Liu, Fuhao Mo

“…In the example of this paper, after the optimization of the established meshless model, the mass of the whole vehicle is reduced by 30%, and the stiffness of the whole vehicle is greater than that of the benchmark vehicle (5128 N/mm, 4386 N/mm), and at the same time, compared with the conceptual design method of the body of CAE technology, the modeling time is greatly reduced, and the computational efficiency of the analytical method is greatly improved compared with the finite element method.…”
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Hidden-layer configurations in reinforcement learning models for stock portfolio optimization by Patrick Kevin Aritonang, Sudarso Kaderi Wiryono, Taufik Faturohman

“…This study explores the impact of hidden-layer configurations in reinforcement learning models for stock portfolio optimization. Using a portfolio of 45 actively traded stocks in the Indonesian stock market, the performance of four reinforcement learning algorithms—Advantage Actor-Critic (A2C), Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO), and Twin Delayed Deep Deterministic Policy Gradient (TD3)—is evaluated with zero, one, and two hidden layers. …”
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Research and application of optimization of physical education training model based on multi-objective differential evolutionary algorithm by Man Wu

“…In order to study the application of the multi-objective differential evolution algorithm in the field of sports transportation. Based on the improvement of multi-objective differential evolution algorithm, this paper proposes the training model of PE education, and compares the prediction results and the actual results. …”
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Integrated Landslide Risk Assessment via a Landslide Susceptibility Model Based on Intelligent Optimization Algorithms by Xin Dai, Jianping Chen, Tianren Zhang, Chenli Xue

“…This study proposes an integrated landslide risk assessment via a landslide susceptibility model based on intelligent optimization algorithms. …”
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Emotion recognition with a Randomized CNN-multihead-attention hybrid model optimized by evolutionary intelligence algorithm by Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Filippo Sanfilippo

“…To address these challenges, we propose an innovative emotion recognition framework that integrates a Randomised Convolutional Neural Network (RCNN) with a Multi-Head Attention model, further optimized by the Football Team Training Algorithm (FTTA) metaheuristic to enhance network parameters effectively. …”
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Enhanced air quality prediction using adaptive residual Bi-LSTM with pyramid dilation and optimal weighted feature selection by R. Sudha, Ajith Damodaran, Gunaselvi Manohar

“…At first, the data for predicting air quality are collected from the relevant data sources. The proposed model introduces a novel methodology for weighted feature selection utilizing an Improved Gannet Optimization Algorithm (IGOA) aimed at enhancing the performance of data classification. …”
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Predictive Performance of Anti-Lock Braking System with PID Controller Optimized by Gravitational Search Algorithm for a Quarter Car Model: Simulation Modeling and Control by Mohd Sabirin Rahmat, Fauzi Ahmad, Vimal Rau Aparow, Rizauddin Ramli, Sallehuddin Mohamed Haris, Mohd Anas Mohd Sabri, Mohd Anas Mohd Sabri, Meor Iqram Meor Ahmad, Mohd Muhyidin Mustafa

“…This research addresses these issues by developing an ABS model using a quarter-car framework incorporated with a PID controller optimized by using Gravitational Search Algorithm (GSA). …”
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Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi

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Performance Improvement in a Vehicle Suspension System with FLQG and LQG Control Methods by Tayfun Abut, Enver Salkım, Andreas Demosthenous

“…The optimum values of the coefficients of the points where the membership functions of the LQG and Fuzzy LQG methods touch were obtained using the grey wolf optimization (GWO) algorithm. The success of the control performance rate of the applied methods was compared based on the passive suspension system. …”
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Distributed data trading algorithm based on multi-objective utility optimization by Xiaohong HUANG, Yong ZHANG, Desheng SHAN, Yekui QIAN, Lu HAN, Dandan LI, Qun CONG

“…The traditional centralized data trading models are not well applicable to the current intelligent era where everything is interconnected and real-time data is generated, and in order to maximize the use of collected data, it is essential to design an effective data trading framework.Therefore, a distributed data trading framework based on consortium blockchain was proposed, which realized P2P data trading without relying on a third party.Aiming at the problem that existing data trading models only consider the factors of the data itself and ignore the factors related to user tasks, a bi-level multi-objective optimization model was constructed based on multi-dimensional factors, such as data quality, data attributes, attribute relevance and consumer competition, to optimize the utilities of data provider (DP) and data consumer (DC).To solve the above model, an improved multi-objective genetic algorithm-collaborative NSGAII was proposed, calculated by the cooperation of DP, DC and data aggregator (AG).The simulation results show that the collaborative NSGAII achieves better performance in terms of the utilities of DP and DC, thus realizing more effective data trading.…”
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Toward a conceptual model to improve the user experience of a sustainable and secure intelligent transport system by Abdullah Alsaleh

“…By leveraging cloud computing and vehicular networks, intelligent transportation solutions optimize traffic flow, improve emergency response systems, and forecast potential collisions, contributing to safer and more efficient roads. …”
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Dynamic Modeling and Parameter Optimization of Potato Harvester Under Multi-Source Excitation by Jianguo Meng, Zhipeng Li, Zheng Li, Yanzhou Li, Wenxia Xie

“…On this basis, the Bayesian optimization algorithm was used to obtain optimal connection parameters. …”
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The Path Tracking Control of Unmanned Surface Vehicles Based on an Improved Non-Dominated Sorting Genetic Algorithm II-Based Multi-Objective Nonlinear Model Predictive Control Meth... by Yunzhe Guo, Qidan Zhu, Jinyou Mou

“…This paper proposes a multi-objective nonlinear model predictive control (MOMPC) method based on an improved non-dominated sorting genetic algorithm II (NSGAII) for the path tracking problem of unmanned surface vehicles (USVs). …”
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Intelligent Teaching Recommendation Model for Practical Discussion Course of Higher Education Based on Naive Bayes Machine Learning and Improved <i>k</i>-NN Data Mining Algorithm by Xiao Zhou, Ling Guo, Rui Li, Ling Liu, Juan Pan

“…Then, relying on the student grouping, we use the matching features between the students’ interest vector and the practical topic vector to construct an intelligent teaching recommendation model based on an improved <i>k</i>-NN data mining algorithm, in which the optimal complete binary encoding tree for the discussion topic is modeled. …”
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An Optimized Method for Solving the Green Permutation Flow Shop Scheduling Problem Using a Combination of Deep Reinforcement Learning and Improved Genetic Algorithm by Yongxin Lu, Yiping Yuan, Jiarula Yasenjiang, Adilanmu Sitahong, Yongsheng Chao, Yunxuan Wang

“…It introduces a novel hybrid approach that combines end-to-end deep reinforcement learning with an improved genetic algorithm. Firstly, the PFSP is modeled using an end-to-end deep reinforcement learning (DRL) approach, named PFSP_NET, which is designed based on the characteristics of the PFSP, with the actor–critic algorithm employed to train the model. …”
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Time-Dependent Multi-Center Semi-Open Heterogeneous Fleet Path Optimization and Charging Strategy by Tingxin Wen, Haoting Meng

“…The self-organizing mapping network method is employed to initialize the EV routing, and an improved adaptive large neighborhood search (IALNS) algorithm is developed to solve the optimization problem. …”
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An Improved LEACH Protocol for Optimizing Cluster Head Selection and In-cluster Selection by SHIBing, GAOZelin, SUNYueping, HUANJuan, SUNTao

“…This protocol initially employs the root mean square (RMS) of distance within the energy consumption model to determine the optimal number of cluster heads. …”
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A Spatial–Temporal Time Series Decomposition for Improving Independent Channel Forecasting by Yue Yu, Pavel Loskot, Wenbin Zhang, Qi Zhang, Yu Gao

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An Improved Maximum Power Point Tracking Control Scheme for Photovoltaic Systems: Integrating Sparrow Search Algorithm-Optimized Support Vector Regression and Optimal Regulation fo... by Mingjun He, Ke Zhou, Yutao Xu, Jinsong Yu, Yangquan Qu, Xiankui Wen

“…To satisfy the performance requirements for the current-tracking process, a linear quadratic (LQ) optimal control strategy was applied to design the current regulator based on the PV system’s state-space model. …”
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