Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model by Weizhen Tang, Jie Dai, Yuantai Li

“…Additionally, the SPM chaotic mapping strategy is utilized for population initialization, while the introduction of the golden sine operator variation strategy enhances the local search capabilities of the algorithm. …”
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Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model by Guowei Li, Gang Tang, Jingyu Zhang, Qun Sun, Xiangjun Liu

“…The paper then delves into the realization method of ship heave motion based on PSO-CNN-LSTM, where the convolutional neural network (CNN) is used to extract the features of the input signal, thereby enhancing the multi-source feature fusion ability of the LSTM neural network model. The PSO algorithm is then employed to optimize the network structure and hyperparameters of the convolutional neural network. …”
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Failure thresholds and weak part identification in cascade reservoir system: A risk-based optimization framework by Haibin Wang, Jiahong Liu, Chao Mei, Jia Wang, Tianxu Song

“…Secondly, a dynamic Particle Swarm Optimization-Genetic Algorithm (PSO-GA) model optimizes outflow strategies during flood events. …”
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Adaptive optimization decision system for plate-fin heat Exchangers: An integrated approach to enhancing efficiency and performance by Na Sun, Shuai Zhang, Nan Li, Zijian Li, Meng He, Zhengchun Shen, Ke Wang, Xiaoyong Guo, Wen-Quan Tao

“…The GSA module uses the Sobol method to evaluate the impact of design variables on performance. The optimization module employs the Newton-Raphson-based optimizer (NRBO) and the multi-strategy improved grey wolf optimization algorithm (MIGWO). …”
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Superior terahertz radiation detection through novel micro circular log-periodic antenna engineered with an advanced evolutionary neural network algorithm by Rui Zhou, Jiaqi Wang, Zhemiao Xie, Yonghai Sun, Guanxuan Lu, John T. W. Yeow

“…Abstract In this work, we introduce a novel Micro Circular Log-Periodic Antenna (MCLPA) optimized with an advanced Evolutionary Neural Network (ENN) algorithm, specifically designed to enhance terahertz (THz) radiation detection. …”
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Methodology for Evaluating the Performance of a New Pulse Oximeter Model and Pulse Oximetry Algorithm in Neonates in a Clinical Trial (Exploratory Study) by T. S. Adylov, E. V. Shestak, V. Yu. Starkov

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HiGMA-DADCN: Hirudinaria granulosa multitropic algorithm optimised double attention enabled deep convolutional neural network for psoriasis classification by Soumya C S, Jayanna H S

“…The HiGMA algorithm plays a crucial role in identifying and extracting the most relevant regions of affected skin through optimal segmentation. …”
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Min3GISG: A Synergistic Feature Selection Framework for Industrial Control System Security with the Integrating Genetic Algorithm and Filter Methods by Saiprasad Potharaju, Swapnali N. Tambe, G. Madhukar Rao, M. V. V. Prasad Kantipudi, Kalyan Devappa Bamane, Mininath Bendre

“…Initially, a Genetic Algorithm (GA) identified 118 relevant features. Further refinement was conducted using filter-based methods—Symmetrical Uncertainty (SU), Information Gain (IG), and Gain Ratio (GR)—leading to a final subset of 104 optimal features. …”
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Using PAT for Energy Recovery and Pressure Reduction in Water Distribution Networks by Hamed Mohammadi, Mahnaz Ghaeini-Hessaroeyeh, Ehsan Fadaei-Kermani

“…Pressure reduction in water distribution networks is usually done using Pressure reducing valve (PRV), while the energy dissipated from head loss can be recovered to generate hydropower. …”
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Modern approaches to the diagnosis and treatment of cardiac sarcoidosis: results of a cohort study by S. V. Mairina, D. V. Ryzhkova, L. B. Mitrofanova, A. V. Ryzhkov, P. M. Murtazalieva, O. M. Moiseeva

“…To analyze clinical and paraclinical data in patients with documented cardiac sarcoidosis, outlining the key points of diagnosis and selection of the optimal treatment.Material and methods. For the period from 2016 to 2021, 63 patients (50,4±14,1 years) were included in the cohort study on negotiability. …”
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A Hybrid Deep Learning-ViT Model and A Meta-Heuristic Feature Selection Algorithm for Efficient Remote Sensing Image Classification by Bilal Ahmed, Syed Rameez Naqvi, Tallha Akram, Lu Peng, Fahdah Almarshad

“…Abstract Recent deep learning techniques driven by large datasets demonstrate the significant impact of feature learning in remote sensing for land use and cover classification, particularly exemplified by CNNs. While the pre-trained models showed good classification performance, they struggled to classify remote-sensing images with high precision accurately. …”
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Exploring explainable machine learning algorithms to model predictors of tobacco use among men in Sub Sahara Africa between 2018 and 2023 by Mequannent Sharew Melaku, Nebebe Demis Baykemagn, Lamrot Yohannes, Adem Tsegaw Zegeye

“…STATA version 17 was used for data cleaning and descriptive statistics, while Python 3.9 was employed for machine learning predictions. …”
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Utilizing molecular simulation, ideal adsorbed solution theory and ensemble learning algorithms to investigate adsorption and separation of sulfides on amorphous nanoporous materia... by Xuan Peng, Xingbang Zhang

“…Using grand canonical Monte Carlo method, we investigated the adsorption of pure H2S and SO2 gases on amorphous materials, and the separation of CH4-H2S and CO2-SO2 mixtures. At 303 K, the optimal adsorbent for both gases was found to be HCP-Colina-id016, with 16 mmol/g. …”
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Life cycle low-carbon capacity optimization planning of integrated energy systems in manufacturing enterprise parks by Tianyi Ma, Jianxiong Qiu, Hu Wang, Lijun Zhang, Xiaojie Lin, Yanling Wu, Hongfei Zhao, Wei Zhong, Yanxin Wang, Zitao Yu, Changhe Zhou, Jian Cheng, Liuliu Du-Ikonen, Xiaolei Yuan

“…The optimization is solved using Non-dominated Sorting Genetic Algorithm II (NSGA-II) combined with the entropy weight method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). …”
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Deceptive Cyber-Resilience in PV Grids: Digital Twin-Assisted Optimization Against Cyber-Physical Attacks by Bo Li, Xin Jin, Tingjie Ba, Tingzhe Pan, En Wang, Zhiming Gu

“…A non-dominated sorting genetic algorithm (NSGA-III) is employed to achieve Pareto-optimal solutions, ensuring high system resilience while minimizing computational burdens. …”
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Optimization of Remote Backup Protection Coordination Logic Based on Dynamic Identification of Faulty Components in Transmission Grids by LIN Xiangning, JI Jihao, DING Yifan, LI Zhengtian, WENG Hanli

“…For symmetrical faults， the traveling wave ranging error is less than 100 m， and the location time is reduced by 90% compared with traditional methods. After optimization， the remote backup-action delay was reduced from 4-7 intervals to 2 intervals， while the setting coverage increased by 18.4%， effectively avoiding misoperations owing to load intrusion. …”
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Microstrip Patch Antenna Design Using a Four-Layer Feed Forward Artificial Neural Network Trained by Levenberg-Marquardt Algorithm by Jitu Prakash Dhar, Maodudul Hasan, Eisuke Nishiyama, Ichihiko Toyoda

“…The ANN contains a multi-layered network architecture that learns and generalizes complex patterns through the LM algorithm and weight optimization based on the datasets without any feature extraction like Deep Neural Network (DNN). …”
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Enhancing Fuzzy C-Means Clustering with a Novel Standard Deviation Weighted Distance Measure by Ahmed Husham Mohammed, Marwan Abdul Hameed Ashour

“…It was proven  through the experimental results that  the proposed distance measure Weighted Euclidean distance  had the advantage over improving the work of the HFCM algorithm through the criterion (Obj_Fun, Iteration, Min_optimization, good fit clustering and overlap) when (c = 2,3) and according to the simulation results, c = 2 was chosen to form groups for the real data, which contributed to determine the best objective function (23.93, 22.44, 18.83) at degrees of fuzzing (1.2, 2, 2.8), while according to the degree of fuzzing (m = 3.6), the objective function for Euclidean Distance (ED) was the lowest, but the criteria were (Iter. = 2, Min_optimization = 0 and )  which confirms that (WED) is the best.…”
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Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm by Roozbeh Moazenzadeh, Okan Mert Katipoğlu, Ahmadreza Shateri, Hamid Nasiri, Mohammed Abdallah

“…This study aimed to develop an accurate and reliable model for predicting suspended sediment load (SL) in river systems, which is crucial for water resource management and environmental protection. While Xtreme Gradient Boosting (XGB), a powerful ensemble machine learning (ML) model, has been employed in previous studies, the novelty of this research lies in the introduction of a hybrid approach that synergistically combines XGB with the bio-inspired Marine Predators Algorithm (XGB-MPA) to estimate SL in the Yeşilirmak River (Turkey). …”
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Landslides in the Himalayas: The Role of Conditioning Factors and Their Resolution in Susceptibility Mapping by Lalit Pathak, Badri Baral, Kamana Joshi, Dipak Raj Basnet, Danilo Godone

“…Sixteen factors, encompassing topography, hydrology, geology, and anthropogenic activities, were analyzed alongside a landslide inventory of 159 occurrences compiled from satellite imagery, the literature, and field surveys. A genetic algorithm (GA) was employed to determine the optimal set of conditioning factors, while Maximum Entropy (Maxent) modeling produced landslide susceptibility maps (LSM) at spatial resolutions ranging between 12.5 and 200 m. …”
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