Data-Adaptive Dynamic Time Warping-Based Multivariate Time Series Fuzzy Clustering by Qinglin Cai, Leiying Chen, Jian Shao, Ling Chen

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Tackling multimodal device distributions in inverse photonic design using invertible neural networks by Michel Frising, Jorge Bravo-Abad, Ferry Prins

“…Importantly, traditional optimization routines assume an invertible mapping between the design parameters and response. …”
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Feature Variable Selection Based on VIS-NIR Spectra and Soil Moisture Content Prediction Model Construction by Nan Zhou, Jin Hong, Bo Song, Shichao Wu, Yichen Wei, Tao Wang

“…To forecast the moisture content of loess on the soil surface, models like partial least squares regression (PLSR), support vector machine (SVM), and random forest (RF) were created. …”
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Light-GBM based minority oversampling model using biomedical data analysis for breast cancer classification by Mukesh Soni, Mohammed Wasim Bhatt, Paul Ofori-Amanfo

“…A model for the identification of breast cancer based on the lightweight gradient boosting machine (GBM) algorithm. …”
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ML-Driven Energy Savings for Cellular Baseband Units via Traffic Prediction by Aneta Kolackova, Viet Anh Phan, Jan Jerabek, Sergey Andreev, Jiri Hosek

“…PESBiU 2.0 uses granular interval datasets and machine learning (ML) models to predict traffic loads and optimize power states. …”
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Identifying behavior regulatory leverage over mental disorders transcriptomic network hubs toward lifestyle-dependent psychiatric drugs repurposing by Mennatullah Abdelzaher Turky, Ibrahim Youssef, Azza El Amir

“…The top disease genes of both MDD and PTSD modules were detected using random forest model. Afterward, the regulatory signature of two predominant habitual phenotypes, diet-induced obesity and smoking, were identified. …”
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From Lab to Clinic: How Artificial Intelligence (AI) Is Reshaping Drug Discovery Timelines and Industry Outcomes by Doni Dermawan, Nasser Alotaiq

“…<b>Results:</b> AI methods included machine learning (ML) at 40.9%, molecular modeling and simulation (MMS) at 20.7%, and deep learning (DL) at 10.3%. …”
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Evolutionary fuzzy learning for Chinese medicine liver syndrome differentiation by Jia-Yu Yan, Peng-Wei Zhang, Wei-Guo Sheng, Jun-Ping Shi, Wei Ni, Li Li, Yu-Jun Zheng

“…To determine the most appropriate fuzzy membership functions of the fuzzy learning machines, an evolutionary algorithm was employed to optimize the types and parameters of the fuzzy functions simultaneously. …”
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HYDRAULIC UNITS FOR DRIVING SYSTEMS OF RUNNING EQUIPMENT IN ROAD CONSTRUCTION MACHINERY by A. Ja. Kotlobai, A. A. Kotlobai, V. F. Tamelo

“…The developed mathematical model and methodology for determination of parameters for the discrete flow distributor allow to optimize its design. …”
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A deep learning model for fault detection in distribution networks with high penetration of electric vehicle chargers by Seyed Amir Hosseini, Behrooz Taheri, Seyed Hossein Hesamedin Sadeghi, Adel Nasiri

“…In this method, first, the features of voltage and current waveforms in various operational scenarios are extracted through a two-dimensional modeling. These features are then used to train a deep learning model based on black widow optimization bi-directional long short-term memory (BWO-BiLSTM) technique. …”
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Predicting Social Media Popularity With Large Language Models: Transforming Metadata Into Semantic-Enriched and Contextualized Text by Tianjian Chen, Jiang Huang, Xuetong Wu, Changcheng Shao

“…Our principal innovation lies in substantially elevating the precision of social media popularity predictions by incorporating comprehensive semantic data descriptions into the modeling process. The LoRA-based approach enables efficient task-specific optimization while preserving the extensive knowledge base of the pre-trained models. …”
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How to Better Use Canopy Height in Soybean Biomass Estimation by Yanqin Zhu, Fan Fan, Zhen Zhang, Xun Yu, Tiantian Jiang, Liming Li, Yadong Liu, Yali Bai, Ziqian Tang, Shuaibing Liu, Dameng Yin, Xiuliang Jin

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Ensemble boosting-based soft-computing models for predicting the bond strength between steel and CFRP plate by Irwan Afriadi, Chanachai Thongchom, Divesh Ranjan Kumar, Suraparb Keawsawasvong, Warit Wipulanusat

“…The study uses a database of 317 experimental datasets compiled from previous literature for training and testing the proposed machine learning models. On the other hand, rank analysis was utilized to determine the optimal models. …”
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Retrieval of water quality parameters based on IOA-ML models and their response to short-term hydrometeorological factors by Wentong Hu, Donghao Miao, Chi Zhang, Zixian He, Wenquan Gu, Dongguo Shao

“…Study focus: Large-scale and high-precision estimation of water quality parameters (WQPs) is critical in explaining the spatiotemporal dynamics and clarifying their response to short-term hydrometeorological factors. Six machine learning models optimized by intelligent optimization algorithms (IOA-ML) were developed to retrieve WQPs using paired in situ measurements and near-synchronous Sentinel-2 reflectance (Rrs). …”
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AI-Driven Optimization of Fly Ash-Based Geopolymer Concrete for Sustainable High Strength and CO₂ Reduction: An Application of Hybrid Taguchi–Grey–ANN Approach by Muhammad Usman Siddiq, Muhammad Kashif Anwar, Faris H. Almansour, Muhammad Ahmed Qurashi, Muhammad Adeel

“…This study addresses this challenge by developing machine learning-optimized geopolymer concrete (GPC) using industrial waste fly ash as cement replacement. …”
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Thyroid nodule classification in ultrasound imaging using deep transfer learning by Yan Xu, Mingmin Xu, Zhe Geng, Jie Liu, Bin Meng

“…Feature screening and dimensionality reduction were conducted using the least absolute shrinkage and selection operator (LASSO) regression method. To identify the optimal model, both traditional machine learning and transfer learning approaches were employed, followed by model fusion using post-fusion techniques. …”
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Wear fault diagnosis in journal bearings using vibration analysis and AI by Jebur Nazik A., Soud Wafa A.

“…In this study, machine learning models for identifying wear defects in journal bearings under various operating circumstances are compared. …”
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A Multi-Objective Black-Winged Kite Algorithm for Multi-UAV Cooperative Path Planning by Xiukang Liu, Fufu Wang, Yu Liu, Long Li

“…In UAV path-planning research, it is often difficult to achieve optimal performance for conflicting objectives. Therefore, the more promising approach is to find a balanced solution that mitigates the effects of subjective weighting, utilizing a multi-objective optimization algorithm to address the complex planning issues that involve multiple machines. …”
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Estimating QoE from Encrypted Video Conferencing Traffic by Michael Sidorov, Raz Birman, Ofer Hadar, Amit Dvir

“…This paper addresses these challenges by analyzing a large dataset of Zoom sessions and training five classical machine learning (ML) models and two custom deep neural networks (DNNs) to predict three QoE indicators: frames per second (FPS), resolution (R), and the naturalness image quality evaluator (NIQE). …”
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Predicting recurrence risk in endometrial cancer: a multisequence MRI intratumoral and peritumoral radiomics nomogram approach by Jie Li, Jie Li, Dianpei Ma, Dianpei Ma, Xiuting Chen, Xiuting Chen, Junting Wei, Junting Wei, Jiali Xu, Yingming Zhao, Zhizhen Gao

“…Nine machine learning classifiers were employed to construct the intratumoral model (RM1). …”
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