Grading Algorithm for Orah Sorting Line Based on Improved ShuffleNet V2 by Yifan Bu, Hao Liu, Hongda Li, Bryan Gilbert Murengami, Xingwang Wang, Xueyong Chen

“…This study proposes a grading algorithm for Orah sorting lines based on machine vision and deep learning. …”
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Vehicle Target Tracking Algorithm Based on Improved Strong Tracking Unscented Kalman Filter by Feng Tian, Siyuan Wang, Weibo Fu, Tianyu Wei

“…A multidimensional adaptive factor-based strong tracking UKF (MAST-UKF) algorithm is proposed. The method introduces multidimensional attenuation factors in the prediction and updating process of filtering, and realizes the strong tracking filtering of vehicle targets by adjusting the uncertainty of state noise covariance and observation noise covariance and dynamically updating the multidimensional attenuation factors by adaptively adjusting the threshold based on the observation residuals and the state estimation error. …”
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Inventory control strategy based on neural network and fuzzy algorithm in intelligent warehousing system by Chunmei Xie, Cong Xie

“…Abstract To cope with the inventory control problem of an intelligent warehousing system, this paper proposes a neuro-fuzzy dynamic inventory regulation model (NFDIRM), which integrates radial basis function neural network (RBFNN) and fuzzy logic algorithm, aiming to solve the problems of poor prediction accuracy and poor decision flexibility of traditional models. …”
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A novel multi-label classification algorithm based on -nearest neighbor and random walk by Zhen-Wu Wang, Si-Kai Wang, Ben-Ting Wan, William Wei Song

“…One challenge of using the random walk-based multi-label classification algorithms is to construct a random walk graph for the multi-label classification algorithms, which may lead to poor classification quality and high algorithm complexity. …”
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Hypertension Detection Using Passive-Aggressive Algorithm With The PA-I And PA-II Methods by M. Hafidz Ariansyah, Sri Winarno

“…This algorithm can work well for learning by transforming data and dealing with unbalanced classification problems. …”
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Low-Light Image Enhancement Algorithm Integrating Retinex Illumination Estimation and Multi-Attention by Yaping Jiang, Shixian Guo

“…The algorithm introduces a perturbation component into the Retinex model to simulate image degradation, enabling more accurate illumination estimation. …”
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Lightweight visible damage detection algorithm for embedded systems applied to pipeline automation equipment by Jiale Xiao, Lei Xu, Changyun Li, Ling Tang, Guogang Gao

“…The backbone of the algorithm, CSPHet, employs efficient combinatorial convolution and heterogeneous kernel convolution, incorporates a lightweight convolutional structure SL in the neck of the network, enhances the nonlinear representation and feature processing capability through channel shuffling, utilizes the lightweight self-attention mechanism Detect_SA for prediction, and employs a multilayered GhostConv to improve the computational efficiency. …”
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An Improved Interpolation Algorithm for Surface Meteorological Observations via Fuzzy Adaptive Optimisation Fusion by Xiaoya Jiang, Xiong Xiong, Wenlan Wang, Xiaoling Ye, Xin Chen, Yihu Wang, Fangjian Zhang

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Enhancing tool condition monitoring in friction stir welding with probabilistic neural network algorithm by Balachandar Krishnamurthy, Jegadeeshwaran Rakkiyannan

“…A feature importance study is conducted using a decision tree algorithm, which selects only the most significant features to reduce computational complexity.ResultFeature classification is then performed using various machine learning and deep learning algorithms, including Support Vector Machines (SVM), Multi-Layer Perceptron (MLP), Cascade Correlation, GMDH Polynomial Neural Networks, and Linear Discriminant Analysis Among these classifiers, Probabilistic Neural Networks (PNN) consistently deliver the best results as 91.25% under 1,400 rpm.DiscussionBased on these findings, the Probabilistic Neural Network algorithm is identified as a robust and reliable prediction model for monitoring FSW tool conditions.…”
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Design of netted muskmelon digital twin growth model based on HMM+LSTM algorithm by LU Peng, LIU Mingtang, WU Shanshan, LI Bin, LI Shihao, WANG Changchun, YANG Yangrui, JIANG Enhui

“…The digital twin model was developed using 3ds Max for 3D modeling and Unity 3D for visualization, while the growth prediction model was built by integrating Hidden Markov Model (HMM) and Long Short-Term Memory (LSTM) algorithms. …”
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Surface Defect Detection Algorithm for Wind Turbine Blades Based on HSCA-YOLOv7 by Bing LI, Yunshan BAI, Kuan ZHAO, Congbin GUO, Yongjie ZHAI

“…The experimental results show that the mAP and mAR of the proposed algorithm reach 83.64% and 71.96%, respectively, which are 3.37% and 5% higher than the YOLOv7 baseline algorithm.…”
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An Explainable LSTM-Based Intrusion Detection System Optimized by Firefly Algorithm for IoT Networks by Taiwo Blessing Ogunseyi, Gogulakrishan Thiyagarajan

“…Specifically, we employ a hybrid approach using statistical methods and a metaheuristic algorithm for feature selection to identify the most relevant features and limit the overall feature set while building an LSTM-based model for intrusion detection. …”
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An Iterative Shifting Disaggregation Algorithm for Multi-Source, Irregularly Sampled, and Overlapped Time Series by Colin O. Quinn, Ronald H. Brown, George F. Corliss, Richard J. Povinelli

“…This process repeats, refining estimates with each iteration cycle. The ISD algorithm’s key contribution is its ability to disaggregate multiple, nonuniformly spaced time series with overlapping intervals into a single daily representation. …”
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Validation of a Novel Data-Driven Algorithm to Detect Atypical Prescriptions in Radiation Therapy by Connor Thropp, MS, Jaroslaw Hepel, MD, Timothy Leech, Eric E. Klein, PhD, Qiongge Li, PhD

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Modelling Soil Water Retention Using Support Vector Machines with Genetic Algorithm Optimisation by Krzysztof Lamorski, Cezary Sławiński, Felix Moreno, Gyöngyi Barna, Wojciech Skierucha, José L. Arrue

“…For the purpose of models’ parameters search, genetic algorithms were used as an optimisation framework. A new form of the aim function used for models parameters search is proposed which allowed for development of models with better prediction capabilities. …”
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An effective parameter estimation on thermoelectric devices for power generation based on multiverse optimization algorithm by Luis Fernando Grisales-Noreña, Vanessa Botero-Gómez, Rubén Iván Bolaños, Faustino Moreno-Gamboa, Daniel Sanin-Villa

“…This study explores using the Multiverse Optimization Algorithm to estimate the material properties of thermoelectric generators used for power generation. …”
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Optimization of IMU-based bending strain solving algorithm and full-scale experimental validation by Tong SHI, Xiaoben LIU, Lin ZHANG, Jun WANG, Rui LI, Ting Xie, Qingshan FENG, Qiyu HUANG

“…Furthermore, the full-scale pulling experiments conducted to validate the algorithm revealed substantial reductions in errors between bending strains computed by the optimized solving algorithm and those detected by a strain gauge at 79.6%, 79.4%, and 76.0%, respectively. …”
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Detection algorithm for wearing safety helmet under mine based on improved YOLOv5s by Yuanbin WANG, Sixiong WEI, Huaying WU, Yu DUAN, Meng LIU

“…Aiming at the problems of low accuracy and high missed detection rate of personnel safety helmet detection algorithm caused by complex environment under mine, an improved mine safety helmet detection algorithm based on YOLOv5s is proposed. …”
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Personalized Recommendation Algorithm for Cultural and Creative Products Based on Fuzzy Decision Support System by Lin Shi, Xiaoqing Yang

“…Hence, this study proposes a fuzzy context-aware neural recommendation algorithm (F-CANRA) to analyze consumers’ purchase behaviors regarding cultural and creative products (CCPs). …”
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Risk of AI Algorithmic Discrimination Embedded in Government Data Governance and Its Prevention and Control by PENG Lihui, ZHANG Qiong, LI Tianyi

“…[Purpose/Significance] The purpose of this study is to provide an in-depth analysis of the widespread application of artificial intelligence (AI) technology in the field of government data governance and its far-reaching implications, with a particular focus on the core issue of algorithmic discrimination. With the rapid development of AI technology, it has demonstrated great potential in government decision support, public service optimization, and policy impact prediction, but it has also sparked extensive debate on issues such as algorithmic bias, privacy invasion, and fairness. …”
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