Computational intelligence analysis on drug solubility using thermodynamics and interaction mechanism via models comparison and validation by Ahmad J. Obaidullah, Wael A. Mahdi

“…In addition, the Fireworks Algorithm (FWA) is presented as an optimization method, demonstrating its potential in improving the model’s predictive abilities by effectively exploring and exploiting the search space. …”
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Research on Pose Error Modeling and Compensation of Posture Adjustment Mechanism Based on WOA-RBF Neural Network by Hongyu Shen, Honggen Zhou, Yiyang Jin, Lei Li, Bo Deng, Jiawei Xu

“…Therefore, a compensation method based on the whale optimization algorithm optimized radial basis function neural network is proposed. …”
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Optimisation of decision making for construction projects of assembly buildings based on improved PSO algorithm by Peng Wang

“…The improved particle swarm algorithm converges to an optimal solution of –19.208 within 20 iterations on the Holder function, with an optimal domain of [8.055, –9.665]. …”
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Swarm Intelligence Algorithms for Optimization Problems a Survey of Recent Advances and Applications by Mande Smita Samrat, M Srinivasulu, Anand Sruthi, K Anuradha, Tiwari Mohit, U Esakkiammal

“…For many years swarm intelligence (SI) algorithms have shown successful performance for complex optimization problems in many fields. …”
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A Betweenness Calibration Topology Optimal Control Algorithm for Wireless Sensor Networks by Ting Yang, Zhixian Lin, Bo Yuan

“…Based on the complex network theory, this paper proposed a novel betweenness addition edges expansion algorithm (BAEE). With betweenness calibration, BAEE algorithm expanded the minimum-cost edges to optimize the network topology. …”
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Regression Test Suite Minimization Using Modified Artificial Ecosystem Optimization Algorithm by Abhishek Singh Verma, Ankur Choudhary, Shailesh Tiwari

“…This paper proposes an effective approach for regression test suite minimization using Artificial Ecosystem Optimization algorithm. To improve its performance a modified Artificial Ecosystem Optimization algorithm is proposed for Test case minimization. …”
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The optimal dispatching strategy of cogeneration based on Deep Q-Network (DQN) algorithm by Zhang Pei, Fu Yan, Yao Fu

“…Acknowledging the constraints of flexibility in winter heating, the study aims to improve unit coal use optimization and lower emissions. …”
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Benchmarking Metaheuristic Algorithms Against Optimization Techniques for Transportation Problem in Supply Chain Management by Felicia Lim Xin Ying, Suliadi Firdaus Sufahani

“…The optimization of transportation problems plays a significant role in supply chain management (SCM), where minimizing costs and improving efficiency are mandatory. …”
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Multi-Objective Parameter Optimization of Rotary Screen Coating Process for Structural Plates in Spacecraft by Yanhui Guo, Yanpeng Chen, Peibo Li, Xinfu Chi, Yize Sun

“…Considering the thickness and uniformity of the adhesive layer as the objectives, the improved algorithm was used to optimize the prediction model to obtain the optimal process parameters. …”
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Improving EEG based brain computer interface emotion detection with EKO ALSTM model by R. Kishore Kanna, Preety Shoran, Meenakshi Yadav, Mohammad Nadeem Ahmed, Shrikant Burje, Garima Shukla, Anurag Sinha, Mohammad Rashid Hussain, Saifullah Khalid

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An Improved Adaptive Car-Following Model Based on the Unscented Kalman Filter for Vehicle Platoons’ Speed Control by Caixia Huang, Wu Tang, Jiande Wang, Zhiyong Zhang

“…This study proposes an adaptive car-following model based on the unscented Kalman filter algorithm to enable coordinated speed control in vehicle platoons and to address key limitations present in conventional car-following models. …”
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Hybrid Swarm Intelligence and Human-Inspired Optimization for Urban Drone Path Planning by Yidao Ji, Qiqi Liu, Cheng Zhou, Zhiji Han, Wei Wu

“…Specifically, competitive and supportive behaviors are mathematically modeled to enhance particle learning strategies and improve global search capabilities in the mid-optimization phase. …”
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Design and Control for Piezoelectric Energy Harvester Based on a Heuristic Optimization Algorithms by Habeeb Jaber Nekad, Diyah Kammel Shary, Oday Alahmad

“…The model output response is improved after adjusting the PID controller in line with optimization algorithms as compared with the conventional PID controller. …”
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Multi-objective optimization and characteristic analysis of contra-rotating fan double-row blades coupling by Xinyu ZHANG, Hua JIANG, Wuqi GONG

“…The sample set data is used to construct a neural network surrogate model, and the weights and thresholds of the neural network are optimized in combination with the genetic algorithm to improve the generalization ability of the surrogate model. …”
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What Influences Low-cost Sensor Data Calibration? - A Systematic Assessment of Algorithms, Duration, and Predictor Selection by Lu Liang, Jacob Daniels

“…Abstract The low-cost sensor has changed the air quality monitoring paradigm with the capacity for efficient network expansion and community engagement. …”
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Flex-route demand response transit scheduling based on station optimization by HU Di, JIN Wenzhou

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Optimization of Flexible Rotor for Ultrasonic Motor Based on Response Surface and Genetic Algorithm by Bo Chen, Jiyue Yang, Haoyu Tang, Yahang Wu, Haoran Zhang

“…This paper presents an optimization method that combines the Kriging response surface model with a multi-objective genetic algorithm (MOGA). …”
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Optimizing Imbalanced Data Classification: Under Sampling Algorithm Strategy with Classification Combination by Nauval Dwi Primadya, Adhitya Nugraha, Sahrul Yudha Fahrezi, Ardytha Luthfiarta

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Joint beam hopping and coverage control optimization algorithm for multibeam satellite system by Guoliang XU, Feng TAN, Yongyi RAN, Feng CHEN

“…To improve the performance of multibeam satellite (MBS) systems, a deep reinforcement learning-based algorithm to jointly optimize the beam hopping and coverage control (BHCC) algorithm for MBS was proposed.Firstly, the resource allocation problem in MBS was transformed to a multi-objective optimization problem with the objective maximizing the system throughput and minimizing the packet loss rate of the MBS.Secondly, the MBS environment was characterized as a multi-dimensional matrix, and the objective problem was modelled as a Markov decision process considering stochastic communication requirements.Finally, the objective problem was solved by combining the powerful feature extraction and learning capabilities of deep reinforcement learning.In addition, a single-intelligence polling multiplexing mechanism was proposed to reduce the search space and convergence difficulty and accelerate the training of BHCC.Compared with the genetic algorithm, the simulation results show that BHCC improves the throughput of MBS and reduces the packet loss rate of the system, greedy algorithm, and random algorithm.Besides, BHCC performs better in different communication scenarios compared with a deep reinforcement learning algorithm, which do not consider the adaptive beam coverage.…”
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Prediction and optimization of robot processing technology based on neural network and genetic algorithm by Fusen WU

“…The optimal process parameter combination determined through genetic algorithm optimization is a radial cutting depth of 2.28 mm, an axial cutting depth of 2.98 mm, a spindle speed of 9 586.65 r/min and a feed rate of 2 207.67 mm/min. …”
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