A Gradient-Based Optimization Algorithm for Optimal Control Problems With General Conformable Fractional Derivatives by Essia Ben Alaia, Slim Dhahri, Omar Naifar

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Classification and Recognition Method for Bearing Fault based on IFOA-SVM by Wei Zhang, Zhihua Ma

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Machine Learning Performance Analysis for Bagging System Improvement: Key Factors, Model Optimization, and Loss Reduction in the Fertilizer Industry by Ari Primantara, Udisubakti Ciptomulyono, Berlian Al Kindhi

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Using Interpretable Artificial Intelligence Algorithms in the Management of Blunt Splenic Trauma: Applications of Optimal Policy Trees as a Treatment Prescription Aid to Improve Pa... by Vahe S. Panossian, Yu Ma, Bolin Song, Jefferson A. Proaño-Zamudio, Veerle P. C. van Zon, Ikemsinachi C. Nzenwa, Azadeh Tabari, George C. Velmahos, Haytham M. A. Kaafarani, Dimitris Bertsimas, Dania Daye

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Identification method of canned food for production line sorting robot based on improved PSO-SVM by GAO Haiyan, GAO Jinyang, WANG Weicheng

“…By improving the particle swarm optimization algorithm to optimize support vector machine parameters, an optimized support vector machine classification model was obtained. …”
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Automatic Brain Tumor Segmentation from MRI using Greedy Snake Model and Fuzzy C-Means Optimization by C. Jaspin Jeba Sheela, G. Suganthi

“…A mask is formed by thresholding the reconstructed image and is eroded to improve the accuracy of segmentation in Greedy Snake algorithm. …”
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Assimilating Satellite-Based Biophysical Variables Data into AquaCrop Model for Silage Maize Yield Estimation Using Water Cycle Algorithm by Elahe Akbari, Ali Darvishi Boloorani, Jochem Verrelst, Stefano Pignatti

“…Based on our proposed workflow in previous studies, a Gaussian process regression–particle swarm optimization (GPR-PSO) algorithm and global sensitivity analysis were applied to retrieve the fCover and biomass from Sentinel-2 satellite data and to identify the most sensitive parameters in the AquaCrop model, respectively. …”
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Oral cancer detection via Vanilla CNN optimized by improved artificial protozoa optimizer by Yulong Chai, Xiuqing Chai, Lan Zhang, Gang Ye, Fatima Rashid Sheykhahmad

“…Abstract In this study, we propose a new method for oral cancer detection using a modified Vanilla Convolutional Neural Network (CNN) architecture with incorporated batch normalization, dropout regularization, and a customized design structure for the convolutional block. An Improved Artificial Protozoa Optimizer (IAPO) metaheuristic algorithm is proposed to optimize the Vanilla CNN and the IAPO improves the original Artificial Protozoa Optimizer through a new search strategy and adaptive parameter tuning mechanism. …”
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Prediction of the 180 day functional outcomes in aneurysmal subarachnoid hemorrhage using an optimized XGBoost model by Weichong Zhou, Xingfu Liao, Hui Shi, Mingfeng Wang, Yunchong Xiao, Xilu Yu, Yilong Wu, YanYi Liu, Yin Peng, Hai Su

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Theoretical investigations on analysis and optimization of freeze drying of pharmaceutical powder using machine learning modeling of temperature distribution by Turki Al Hagbani, Jawaher Abdullah Alamoudi, Majed A. Bajaber, Huda Ibrahim Alsayed, Halah Jawad Al-fanhrawi

“…Model optimization is achieved through the Fireworks Algorithm (FWA). …”
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Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.) by Fazilat Fakhrzad, Warqaa Muhammed ShariffAl-Sheikh, Mohammed M. Mohammed, Heidar Meftahizadeh

“…Collectively, these findings highlight the potential of integrating machine learning and evolutionary optimization algorithms as powerful computational tools for crop improvement and agronomic decision-making.…”
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Optimization of Teaching Management System Based on Association Rules Algorithm by Qing Niu

“…Second, use the MapReduce calculation model to partition the transaction database, then use the improved Apriori optimization algorithm for mining, and finally merge the mining results to obtain frequent itemsets. …”
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Financial Market Evaluation Utilizing an Optimized Deep-Learning Model: A Case Study of the Nikkei 225 by Karthikeyan M P

“…The precision of the stock market forecasts can be improved using metaheuristic algorithms such as the Moth-flame optimizer, which will provide the best optimization of the hyperparameters for an LSTM model. …”
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Residual Life Prediction of Proton Exchange Membrane Fuel Cell Based on Improved ESN by Tiejiang YUAN, Rongsheng LI, Jiandong KANG, Huaguang YAN

“…Aiming at the problem that the current residual effective life prediction (RUL) technique for proton exchange membrane fuel cells (PEMFCs) has poor prediction effect in the medium and long term, a residual life prediction method based on the Improved Gray Wolf Optimization algorithm (IGWO) and Echo State Network (ESN) is proposed, in which the voltage of the electric stack is firstly selected as a health indicator, and the PEMFC dataset is processed by using convolutional smoothing filtering method to carry out data Smoothing and normalization are used to effectively reduce the interference of outliers on the subsequent model training. …”
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Improving Integrated Energy Systems With Improved Particle Swarm Optimization: Co-Optimizing Renewables, Electric Vehicles, Gas Systems, and Demand Management by Vahid Khademi, Soodabeh Soleymani, Reza Sharifi, Babak Mozafari

“…The I-PSO algorithm improves optimization performance by about 3.4% compared to competing methods, demonstrating its effectiveness in solving complex energy management problems.…”
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Reinforcement learning algorithm for improving speed response of a five-phase permanent magnet synchronous motor based model predictive control. by Ahmed M Hassan, Jafar Ababneh, Hani Attar, Tamer Shamseldin, Ahmed Abdelbaset, Mohamed Eladly Metwally

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Research on Two-Stage Energy Storage Optimization Configurations of Rural Distributed Photovoltaic Clusters Considering the Local Consumption of New Energy by Yang Liu, Dawei Liu, Keyi Kang, Guanqing Wang, Yanzhao Rong, Weijun Wang, Siyu Liu

“…Taking a Chinese village as an example, the proposed model is optimized with an improved particle swarm optimization algorithm. …”
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An Immune Algorithm based Reliability Optimization Method of Circuit Board by XIA Quan, REN Yi, SUN Bo, WU Zeyu

“…This method is applied to solve the reliability optimization model of typical circuit boards, and the optimization scheme of design variables is obtained.The results are compared with genetic algorithm and ant colony algorithm.It shows that the immune algorithm has the advantages of fast convergence speed and strong optimization ability.Moreover, the calculation time is reduced by about 37.2% by the collaborative optimization strategy in the case.Thus, the collaborative optimization method based on immune algorithm proposed in this paper can effectively improve the solution efficiency of circuit board reliability optimization model.…”
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Optimum design of bearingless brushless DC motor modeling with dual loop controller using dragonfly optimizers by Qusay S. Kadhim, Mahmood Swadi, Ali Jafer Mahdi, Mohanad Azeez Joodi, Firas Mohammed Tuaimah, Moanes E. Mohammed, Abbas Hafeth Abbas, Mohamed Salem

“…The proposal's focus consists of two contributions: firstly, the optimal design of the BBLDC motor; secondly, the application of the Dragonfly Algorithm (DA) for the improvement of the motor's control systems, resulting in reduced torque ripple, rapid and precise tracking, and elimination of overshoot. …”
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Robust reinforcement learning algorithm based on pigeon-inspired optimization by Mingying ZHANG, Bing HUA, Yuguang ZHANG, Haidong LI, Mohong ZHENG

“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
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