MKD-Net: A Novel Neuro Evolutionary Approach for Blockchain-Based Secure Medical Image Classification Using Multi-Kernel DLM by Virendra P. Vishwakarma, Abhay Kumar Yadav

“…Owing to advancements in the domain of nature-inspired optimization and human brain simulations, this paper presents a novel approach to a neuro-evolutionary algorithm for medical image classification. …”
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Research status of gearboxes for high-power nuclear power circulation pumps by WEI Fude, WANG Huanhuan, YANG Shuncheng

“…Many scholars are committed to in-depth research on high-power nuclear power circulating pump gearboxes from the perspectives of dynamics, mechanical design, big data, optimization algorithms, etc., in response to the above-mentioned issues. …”
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Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data by W. Bang, J. T. Carlin, K. Kim, A. V. Ryzhkov, A. V. Ryzhkov, G. Liu, G. Lee

“…We thus explore the effects of the SBM's microphysics scheme on the extent of melting in cases of misdiagnosed RA. An optimized SBM that uses the climatological snow density–diameter relationship for the Pyeongchang region produces an increased amount of melting and achieves improved skill scores compared to the current SBM, which uses a snow density–diameter relationship for the Colorado region.…”
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A Deep Neural Network Framework for Dynamic Two-Handed Indian Sign Language Recognition in Hearing and Speech-Impaired Communities by Vaidhya Govindharajalu Kaliyaperumal, Paavai Anand Gopalan

“…Using the Tuna Swarm Optimization (TSO) algorithm in its enhanced form, the provided Enhanced Convolutional Transformer (ECT) model is optimally tuned to handle the problem dimensions with convergence problem parameters. …”
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A Matching Game for LLM Layer Deployment in Heterogeneous Edge Networks by Benedetta Picano, Dinh Thai Hoang, Diep N. Nguyen

“…Executing the inference of foundation models in a distributed manner presents significant challenges, particularly in optimizing both computing and communication resources. …”
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Alpine Meadow Fractional Vegetation Cover Estimation Using UAV-Aided Sentinel-2 Imagery by Kai Du, Yi Shao, Naixin Yao, Hongyan Yu, Shaozhong Ma, Xufeng Mao, Litao Wang, Jianjun Wang

“…Subsequently, four machine learning models were employed for an accurate FVC inversion, using the estimated FVC values and UAV-derived reference FVC as inputs, following feature importance ranking and model parameter optimization. …”
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Development of Flash Flood Forecasting System for Small and Medium‐Sized Rivers by Koji Ikeuchi, Daiki Kakinuma, Yosuke Nakamura, Shingo Numata, Takafumi Mochizuki, Keijiro Kubota, Masaki Yasukawa, Toshihiro Nemoto, Toshio Koike

“…This forecasting approach uses the rainfall–runoff–inundation (RRI) model and the H–Q equation. The parameters in the RRI model were optimized using the Shuffled Complex Evolution algorithm developed at the University of Arizona (SCE‐UA) to reduce the required time and effort. …”
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Edge-Fog Computing-Based Blockchain for Networked Microgrid Frequency Support by Ying-Yi Hong, Francisco I. Alano, Yih-der Lee, Chia-Yu Han

“…The proposed approach integrates an edge–fog hierarchical blockchain architecture with a Long Short-Term Memory Model-Free Predictive Controller (LSTM-MFPC). The parameters and hyperparameters of the LSTM-MFPC are optimized using the Bayesian Adaptive Direct Search (BADS) algorithm. …”
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Causation Analysis of Marine Traffic Accidents Using Deep Learning Approaches: A Case Study from China’s Coasts by Zelin Zhao, Xingyu Liu, Lin Feng, Manel Grifoll, Hongxiang Feng

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Dynamic selectout and voting-based federated learning for enhanced medical image analysis by Saeed Iqbal, Adnan N Qureshi, Musaed Alhussein, Khursheed Aurangzeb, Atif Mahmood, Saaidal Razalli Bin Azzuhri

“…The voting system and the dynamic SelectOut algorithms improve the convergence of the FL model and successfully handle the difficulties presented by uneven and heterogeneous datasets. …”
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A Precise Oxide Film Thickness Measurement Method Based on Swept Frequency and Transmission Cable Impedance Correction by Yifan Li, Qi Xiao, Lisha Peng, Songling Huang, Chaofeng Ye

“…A swept frequency signal-processing algorithm is developed to separate the parameters and calculate oxide film thickness. …”
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LDDFSF-YOLO11: A Lightweight Insulator Defect Detection Method Focusing on Small-Sized Features by Peng Shen, Keyu Mei, Huiqiong Cao, Yongxiang Zhao, Guoqing Zhang

“…And optimize the network structure through channel pruning technology to improve model lightweighting. …”
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Acute kidney disease in hospitalized pediatric patients: risk prediction based on an artificial intelligence approach by Lingyu Xu, Siqi Jiang, Chenyu Li, Xue Gao, Chen Guan, Tianyang Li, Ningxin Zhang, Shuang Gao, Xinyuan Wang, Yanfei Wang, Lin Che, Yan Xu

“…Predictive models were constructed using eight machine learning algorithms and two ensemble algorithms, with the optimal model identified through AUROC. …”
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ECMS-Based MPC Strategy for Multi-Mode Hybrid Electric Trucks by Longjian Li, Changqing Du, Xiangyu Gongye, Jinhai Wang

“…To address the adaptive energy management optimization challenge of a hybrid powertrain system consisting of an internal combustion engine and dual electric motors, an Equivalent Consumption Minimization Strategy (ECMS) is introduced into the Model Predictive Control (MPC) framework. …”
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Deep neural network approach integrated with reinforcement learning for forecasting exchange rates using time series data and influential factors by T. Soni Madhulatha, Dr. Md. Atheeq Sultan Ghori

“…Traditional statistical models (ARIMA), state-of-the-art deep learning methods (LSTM, GRU), and hybrid models (TSMixer, in addition to AB-LSTM-GRU) all exhibit low adaptability to dynamic market conditions, as they cannot perform iterative optimization based on real-time feedback. …”
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Continuous Action Air Combat Maneuver Decision-Making Based on T-MGMM by Junzhe Jiang, Hongming Wang, Zhixing Huang, Zhuangfeng Zhou, Xiang Wu, Wenqin Deng, Xueyun Chen

“…To address these challenges, this paper proposes a novel algorithm, T-MGMM, which integrates Transformer networks with a Multivariate Gaussian Mixture Model (MGMM). …”
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Aircraft Flight Autonomous Decision-Making Method Based on Target Predicted Trajectory and Markov Decision Process by Yang Zhou, Xinmin Tang, Xuanming Ren

“…Firstly, our own aircraft utilizes the IMM algorithm to achieve the state prediction of the target; building upon the existing algorithmic structure, the proposed framework improves model sets within the IMM algorithm by incorporating climb and turn models and refines the motion modes of aircraft during the cruise phase, gathering corresponding sub-models to predict different motion modes and enhance the prediction accuracy of the target. …”
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Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis by Yuxing Liu, Jintao Chen, Daifeng Yang, Chenming Liu, Chunhui Tang, Shanshan Cai, Yingxuan Huang

“…Utilizing transcriptomic and gene expression data from TCGA and GEO databases, 72 immune-related lncRNAs were identified through weighted gene co-expression network analysis (WGCNA) and ImmuLncRNA algorithms. The model was further optimized using 101 combinations of 10 machine learning approaches, ultimately constructing an immune-related lncRNA signature(IRLS) scoring system comprising nine key lncRNAs. …”
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Understanding visitor flow and behaviour in developing tourism-service-oriented villages by space syntax methodologies: a case study of Tabian Rural Section of Qingshan Village, Ha... by Shuqin Wang, Yan Huang, Tianjie Li

“…This study innovatively combines space syntax models for extended application in the research of rural BEs, providing guidance for optimizing strategies to improve spatial configuration in homogeneous villages.…”
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Laser-induced Breakdown Spectroscopy Based on Pre-classification Strategy for Quantitative Analysis of Rock Samples by Weiheng KONG, Lingwei ZENG, Yu RAO, Sha CHEN, Xu WANG, Yanting YANG, Yixiang DUAN, Qingwen FAN

“…Different element quantitative models were constructed for each rock type. The kNN algorithm was selected using cross-validation to determine the optimal k value, and the key punishment parameter C and RBF width parameter γ of the SVM algorithm were determined using a grid search method. …”
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