A Numerical Modeling Study of a New Type of Hydraulic Mechanical Continuously Variable Transmission (HMCVT) with Optimized Transmission Efficiency by Zexin Ma, Zhengyu Li, Deming Sun, Yanbin Cai, Jiwei Zhang, Hongyu Liu, Qingxin Wang, He Li, Long Zhou, Wenbin Yu, Feiyang Zhao

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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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Improving Acceptance to Sensory Substitution: A Study on the V2A-SS Learning Model Based on Information Processing Learning Theory by Kyeong Deok Moon, Yun Kyung Park, Moo Seop Kim, Chi Yoon Jeong

“…This improvement is significantly higher than the gain of 2.72% achieved by optimizing the V2A-SS algorithm with Mel-Scaled Frequency Mapping. …”
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Detection of Irrigated and Non-Irrigated Soybeans Using Hyperspectral Data in Machine-Learning Models by Izabela Cristina de Oliveira, Ricardo Gava, Dthenifer Cordeiro Santana, Ana Carina da Silva Cândido Seron, Larissa Pereira Ribeiro Teodoro, Mayara Favero Cotrim, Regimar Garcia dos Santos, Rita de Cássia Félix Alvarez, Carlos Antonio da Silva Junior, Fábio Henrique Rojo Baio, Paulo Eduardo Teodoro

“…The objectives of this work are (i) to classify soybean cultivars under different irrigation managements using hyperspectral data, looking for the best machine-learning algorithm for the classification and the input that improves the performance of the models. …”
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A novel controllability method on temporal networks based on tree model by Peyman Arebi

“…Evaluation against conventional methods on experimental datasets reveals notable improvements: a 41.8% reduction in the minimum number of control nodes, a 36.37% decrease in time of receiving fully control network, and a 38.5% reduction in control algorithm execution time compared to layered model-based control methods.…”
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Comparative analysis of machine learning models for the detection of fraudulent banking transactions by Pedro María Preciado Martínez, Ricardo Francisco Reier Forradellas, Luis Miguel Garay Gallastegui, Sergio Luis Náñez Alonso

“…Using data from 565,000 real-world transfers, models based on algorithms such as Random Forest, Neural Networks and Naive Bayes were built and tested. …”
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A hybrid model for short-term offshore wind power prediction combining Kepler optimization algorithm with variational mode decomposition and stochastic configuration networks by Bingbing Yu, Yonggang Wang, Jun Wang, Yuanchu Ma, Wenpeng Li, Weigang Zheng

“…Compared with the basic VMD model, the data decomposition efficiency of the optimized VMD model has been improved by 28.86%. …”
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Improving Distribution Prediction by Integrating Expert Range Maps and Opportunistic Occurrences: Evidence From Japanese Sea Cucumber by Bingqing Xiao, Songxi Yuan, Ákos Bede‐Fazekas, Jinxin Zhou, Xingyu Song, Qiang Lin, Lei Cui, Zhixin Zhang

“…We first fitted SDMs for this species based on opportunistic occurrence records via four modeling algorithms, then built two types of ensemble models using stacked generalization: an ensemble model that solely used four model predictions and an expert‐informed ensemble model that further accounted for distance to the IUCN expert range map. …”
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Ensemble learning with RAG model to reduce redundant question topics in auto-generated exam questions by R. Tharaniya Sairaj, S. R. Balasundaram

“…Experimental results on various datasets show that the proposed RAG + T5 model reduces redundant question topics along with an improvement in terms of ROUGE-2 metric (up to 5%) and BERTScore (up to 12%) over existing methods. …”
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Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning by Muhammad Salman Khan, Tianbo Peng, Tianbo Peng, Muhammad Adeel Khan, Asad Khan, Mahmood Ahmad, Mahmood Ahmad, Kamran Aziz, Mohanad Muayad Sabri Sabri, N. S. Abd EL-Gawaad

“…Compared to a baseline model from the literature, O-LGB achieved significant improvements in predictive performance. …”
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A multicenter study on developing a prognostic model for severe fever with thrombocytopenia syndrome using machine learning by Jian-She Xu, Kai Yang, Bin Quan, Jing Xie, Yi-Shan Zheng, Yi-Shan Zheng

“…Twenty-four commonly available clinical features were selected, and the Boruta algorithm identified 12 candidate predictors, ranked by Z-scores, which were progressively incorporated into 10 machine learning models to develop prognostic models. …”
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Analysis of Customer Power Consumption Behavior Based on DPSO-Kmeans under the Ubiquitous Power Internet of Things by WANG Ying, XIANG Wen, ZHANG Qun, GAO Xiuyun

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Application of log-based specific surface area prediction for permeability modeling in a highly heterogeneous carbonate reservoir in the middle east by Mojtaba Homaie, Ida Lykke Fabricius, Morten Leth Hjuler, Asadollah Mahboubi, Ali Kadkhodaie, Reza Moussavi Harami

“…Provided the fractures in the core samples truly represent fractures in the reservoir, permeability modeled using log-based specific surface tends to underestimate permeability, achieving a correlation coefficient of 0.62 for the first method and an improved results (CC = 0.7) from the machine-learning approach.…”
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Optimization Strategy of Multi-group Inspection Path of Distribution Equipment with Equipment Information Included by Chaoqiang CHEN, Hanyang GONG, Di ZHANG, Zhidan ZHANG, Jian LE

“…A distribution equipment information model is established, and a multi group distribution equipment routing optimization model is proposed to minimize the total routing cost, which is solved by genetic algorithm. …”
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Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models by Mohammad Bazrafshan, Kourosh Sayehmiri

“…A combination of statistical models for feature selection and machine learning algorithms for prediction was used, with Random Forest showing the best performance. …”
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A Novel Seal Packaging Structure Applied in Sub Miniature Push-On Connector Based on Ni47Ti44Nb9 Shape Memory Alloy Seal Ring by Yang Hai, Cong Lu

“…Finally, to reduce the seal packaging leakage rate, the structural parameters of the seal ring are further optimized with an improved Adaptive Genetic Algorithm (IAGA), and the efficiency of the IAGA is verified through comparison with the conventional Adaptive Genetic Algorithm (AGA).…”
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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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A Distribution Network Expansion Project Classification Model Based on Data Augmentation and Dimensionality Reduction Method by Xin ZHOU, Jingxing LIN, Zhiwei XIE, Zheng ZHANG, Ruduo LIANG, Zuhong OU

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A Hybrid Approach for Reachability Analysis of Complex Software Systems Using Fuzzy Adaptive Particle Swarm Optimization Algorithm and Rule Composition by Nahid Salimi, Seyfollah Soleimani, Vahid Rafe, Davood Khodadad

“…The application of rule composition further reduced execution time by 35.7% and the number of explored states by 41.2% in large-scale models. These results confirm that proposed hybrid algorithm significantly enhances reachability analysis in the systems modelled via Graph Transformation, improving both computational efficiency and scalability.…”
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A Novel Two-Stage Adaptive Filtering Model-Based GNSS/INS Tightly Coupled Precise Relative Navigation Algorithm for Autonomous Aerial Refueling by Ling Wu, Yongrong Sun, Xiyu Fu, Rui Xu

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