Comparing Models and Performance Metrics for Lung Cancer Prediction using Machine Learning Approaches. by Ruqiya, Noman Khan, Saira Khan

“…It optimizes the performance of models for predicting lung cancer. …”
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A Novel Reactive Power Sharing Control Strategy for Shipboard Microgrids Based on Deep Reinforcement Learning by Wangyang Li, Hong Zhao, Jingwei Zhu, Tiankai Yang

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A Decomposed-Ensemble Prediction Framework for Gate-In Operations at Container Terminals by Yifan Shen, Beng Xuan, Hongtao Hu, Yansong Wu, Ning Zhao, Zhen Yang

“…The experiment compares the autoregressive integrated moving average (ARIMA) algorithm, the prophet algorithm, and the Long Short-Term Memory (LSTM) algorithm, with results indicating the clear advantage of Long Short-Term Memory in decomposed time series modeling. …”
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ARIMA-Kriging and GWO-BiLSTM Multi-Model Coupling in Greenhouse Temperature Prediction by Wei Zhou, Shuo Liu, Junxian Guo, Na Liu, Zhenglin Li, Chang Xie

“…Optimal prediction accuracy was observed in clear weather (RMSE = 0.71 °C), whereas rainy/snowy conditions showed a 42.9% improvement in MAPE compared to the PSO-BP model. …”
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A Robust Adaptive Strategy for Diesel Particulate Filter Health Monitoring Using Soot Sensor Data by Bilal Youssef

“…Different cost functions have been tested and evaluated to improve the diagnostic performance. The proposed adaptive approach is model-free and eliminates the need for subsystem models, iterative algorithms, and extensive calibration procedures. …”
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The synergistic effects of circuit training and diet on weight loss, body fat percentage, and BMI in obese Indonesian females: a randomized controlled trial by Moch Yunus, Nanang Tri Wahyudi, Ronal Surya Aditya, Alifia Candra Puriastuti, Daifallah M. Alrazeeni, Gadis Meinar Sari, Farsya Hidayah Septiananda, Lintang Nirmalasari Gemalochaya Manggolono

“…Conclusion: Smartwatch apps have great potential in optimizing cardiovascular fitness training. Future research needs to focus on improving sensor accuracy, refining AI interventions, and long-term user engagement to maximize their impact.…”
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Integrated Operational Planning of Battery Storage Systems for Improved Efficiency in Residential Community Energy Management Using Multistage Stochastic Dual Dynamic Programming:... by Pattanun Chanpiwat, Fabricio Oliveira, Steven A. Gabriel

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Prediction of lithium-ion battery SOC based on IGA-GRU and the fusion of multi-head attention mechanism by Pei Tang, Minnan Jiang, Weikai Xu, Zhengyu Ding, Mao Lv

“…Compared with the traditional parameter optimization approach, this paper uses the immune genetic algorithm to find the optimal hyperparameters of the model, which on the one hand has a wider choice of parameters, and on the other hand has been improved for the genetic algorithm is easy to fall into the local optimal solution, so as to improve the SOC estimation accuracy of the GRU model. …”
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Hybrid A*-Guided Model Predictive Path Integral Control for Robust Navigation in Rough Terrains by Joonyeol Yang , Minhyeong Kang , Seulchan Lee, Sanghyun Kim

“…This article proposes the Hybrid A*-guided Model Predictive Path Integral (MPPI) algorithm augmented with traversability estimation to address the challenges of path planning on uneven terrains. …”
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A Systematic Integration of Artificial Intelligence Models in Appendicitis Management: A Comprehensive Review by Ivan Maleš, Marko Kumrić, Andrea Huić Maleš, Ivan Cvitković, Roko Šantić, Zenon Pogorelić, Joško Božić

“…Artificial intelligence (AI) and machine learning (ML) are transforming the management of acute appendicitis by enhancing diagnostic accuracy, optimizing treatment strategies, and improving patient outcomes. …”
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Non-destructive identification of commercial jerky types based on multi-band hyperspectral imaging with machine learning by Yuanxi Han, Liang Li, Siyuan Jiang, Pengpeng Sun, Wenliang Wu, Zhendong Liu

“…After data preprocessing, all models' accuracies and stability improved. Specifically, the logistic regression model was best for jerky identification, with 85.78 %–100.00 % accuracy. …”
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Elastic net with Bayesian Density Estimation model for feature selection for photovoltaic energy prediction by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…The findings specify a substantial improvement in accuracy in prediction, emphasizing how the model can be used for improving solar power grid integration and energy for improved RE management.…”
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Biosynthesis, applications, and mathematical modeling dynamics of lactic acid bacteria exopolysaccharides: A review by Ankit Barot, Kalyan Das, Yogesh Patel, et al.

“…These models improve the economic viability of LAB-EPS production by optimizing output and reducing substrate use. …”
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Coordinated multi-level scheduling method considering uncertainty of renewable energy and load by Bingbing Song, Kangping Qin, Min Wen, Moyan Zhu, Kaiming Zou, Guangyu He

“…At the provincial level, a two-stage robust optimization dispatch model is constructed based on regional grid dispatch, and it is solved using the Karush-Kuhn-Tucker conditions and the Column-and-Constraint Generation (C&CG) algorithm. …”
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Evaluation of Knowledge Management Maturity Level in Iranian Audiovisual Archives Based on the APQC Model by Sepideh Ciruskabiri, Atefeh Sharif, Saeed Rezaei Sharifabadi, Mohammad Hassanzadeh

“…In implementing KM, understanding the organization’s current status from the perspective of KM maturity is of paramount importance, since KM maturity models describe the expected steps for organizational improvement in terms of knowledge management.Methodology: In this study, five knowledge management maturity models were analyzed, including the Capability Maturity Model (CMM); the Capability Maturity Model Integration (CMMI); the General Knowledge Management Maturity Model (G-KMMM); the Asian Productivity Organization (APO) model; and finally, the APQC Knowledge Management Maturity Model. …”
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A Tri-Level Transaction Method for Microgrid Clusters Considering Uncertainties and Dynamic Hydrogen Prices by Hui Xiang, Xiao Liao, Yanjie Wang, Hui Cao, Xianjing Zhong, Qingshu Guan, Weiyun Ru

“…A polygonal uncertainty set method quantifies wind and solar energy uncertainties, while an enhanced interval optimization technique refines the model. We integrate a sophisticated demand response model for hydrogen loading, capturing users’ behavior in response to price changes, thereby improving renewable energy utilization and supporting economically viable management practices. …”
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Text intelligent correction in English translation: A study on integrating models with dependency attention mechanism. by Yutong Liu, Shile Zhang

“…The research uses the Conference on Natural Language Learning (CoNLL)-2014 dataset as an experimental benchmark, which contains a rich collection of grammatical error samples and is a standard resource in linguistic research. During model training, the Adam optimization algorithm is employed, and the model's performance is enhanced by introducing a customized dependency self-attention mechanism for parameter optimization. …”
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Enhanced early detection of dysarthric speech disabilities using stacking ensemble deep learning model by Jagat Chaitanya Prabhala, Ravi Ragoju, Venkatanareshbabu Kuppili, Christophe Chesneau

“…Unlike conventional stacking methods that use fixed meta-classifiers, this study employs a Genetic Algorithm (GA)-based optimization strategy to dynamically determine optimal weight contributions of the base models, enhancing classification robustness and adaptability.The preprocessing pipeline converts speech signals from the time domain to the frequency domain by using a Short-Time Fourier Transform (STFT). …”
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A Novel Deep Learning Architecture for Agriculture Land Cover and Land Use Classification from Remote Sensing Images Based on Network-Level Fusion of Self-Attention Architecture by Hussain Mobarak Albarakati, Muhammad Attique Khan, Ameer Hamza, Faheem Khan, Naoufel Kraiem, Leila Jamel, Latifah Almuqren, Roobaea Alroobaea

“…In addition, we proposed a quantum hippopotamus optimization algorithm for the best feature selection. …”
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An intelligent incentive-based demand response program for exhaustive environment constrained techno-economic analysis of microgrid system by Bishwajit Dey, Gulshan Sharma, Pitshou N. Bokoro, Soham Dutta

“…Abstract The cost-effective scheduling of distributed energy resources through sophisticated optimization algorithms is the main focus of recent work on microgrid energy management. …”
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