A Differential Evolution-Oriented Pruning Neural Network Model for Bankruptcy Prediction by Yajiao Tang, Junkai Ji, Yulin Zhu, Shangce Gao, Zheng Tang, Yuki Todo

“…The EPNN possesses a dynamic dendritic structure that is trained by a global optimization learning algorithm: the Adaptive Differential Evolution algorithm with Optional External Archive (JADE). …”
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Dual Strategy Based Improved Swarm Intelligence and Stacked LSTM With Residual Connection for Land Use Land Cover Classification by Vinaykumar Vajjanakurike Nagaraju, Ananda Babu Jayachandra, Andrzej Stateczny, Swathi Holalu Yogesh, Raviprakash Madenur Lingaraju, Balaji Prabhu Baluvaneralu Veeranna

“…This article proposes a dual strategy-based bald eagle search (DSBES) algorithm and stacked long short-term memory (LSTM) with residual connection for LULC classification. …”
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SYMBOLIC ANALYSIS OF CLASSICAL NEURAL NETWORKS FOR DEEP LEARNING by Vladimir Milićević, Igor Franc, Maja Lutovac Banduka, Nemanja Zdravković, Nikola Dimitrijević

“…This unique original method can help scientists and programmers design complex machine learning algorithms and understand how deep learning algorithms work. …”
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A Verifiable and Secure Industrial IoT Data Deduplication Scheme With Real-Time Data Integrity Checking in Fog-Assisted Cloud Environments by Jakkarin Lapmoon, Somchart Fugkeaw

“…Additionally, we introduced a temporal data removal algorithm to manage outdated IoT data effectively, significantly reducing storage costs in fog computing environments. …”
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Qualitative Discrimination of Intact Tobacco Leaves Based on Near-Infrared Technology by Mengyao Lu, Qiang Zhou, Tian’en Chen, Junhui Li, Shuwen Jiang, Qin Gao, Cong Wang, Dong Chen

“…The spectral characteristics and spectral preprocessing methods of intact tobacco leaves are analyzed, and then different spectra (independent or average spectra) and different algorithms (discriminant partial least-squares (DPLS) and Fisher’s discriminant algorithms) are used to construct discriminant models for verifying the feasibility of intact leaf modeling and determining the optimal model conditions. …”
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Predicting Compressive Strength of Concrete Containing Industrial Waste Materials: Novel and Hybrid Machine Learning Model by Mohammed Majeed Hameed, Mustafa Abbas Abed, Nadhir Al-Ansari, Mohamed Khalid Alomar

“…Since the traditional method of calculation CS is complicated and requires lots of effort, this article presents new predictive models called SVR−PSO and SVR−GA, that are a hybridization of support vector regression (SVR) with improved particle swarm algorithm (PSO) and genetic algorithm (GA). Furthermore, the hybrid models (i.e., SVR−PSO and SVR−GA) were used for the first time to predict CS of concrete where the cement component is partially replaced. …”
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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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Interleaved Landsman Converter with Class Topper Optimized PI Control in Sensorless BLDC Motor Drive for Electric Vehicle by Suresh V., Jahnavi V.G., Manjula D., Lokesh M.

“…In order to achieve the set goals, the following tasks were accomplished: The scientific novelty of this work lies in the design of a novel interleaved Landsman converter along with Class Topper Optimization (CTO) algorithm. The converter is designed to optimize power conversion from photovoltaic (PV) sources to the energy required for the BLDC motor; the algorithm is implemented to hyper-tune the PI controller for precise and rapid response; a bidirectional converter was employed to manage the charging and discharging of the battery system, ensuring adequate power distribution during peak demands; and a single-phase voltage source inverter (VSI) was utilized for DC-AC conversion to drive the BLDC motor. …”
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Capacity Factor Forecasting for Generation Facilities Based on Renewable Energy Sources in Decentralized Power Systems by A. M. Bramm, P. V. Matrenin, N. A. Papkova, D. A. Sekatski

“…The present paper proposes a new algorithm for estimating the capacity factor for the entire territory of a certain administrative unit and a model for its forecasting based on climatic and geographical parameters. …”
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Taxation of exports and imports of services: Automation of accounting and audit of transactions by Іryna Zhurakovska, Roman Sydorenko

“…The author proposes an algorithm for preparing information on transactions to verify their correct VAT taxation: identification of the service; determination of the places of registration of counterparties; determination of the place of service provision; determination of the date of service. …”
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Design and Profit Allocation in Two-Echelon Heterogeneous Cooperative Logistics Network Optimization by Yong Wang, Yingying Yuan, Kevin Assogba, Ke Gong, Haizhong Wang, Maozeng Xu, Yinhai Wang

“…First, a mixed integer linear programing model is introduced to minimize the total operating cost of nonempty coalitions. Thus, the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm are hybridized to propose GA-PSO heuristics. …”
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IM-OFDM ISAC Outperforms OFDM ISAC by Combining Multiple Sensing Observations by Hugo Hawkins, Chao Xu, Lie-Liang Yang, Lajos Hanzo

“…Hence, a novel low complexity algorithm is proposed for ensuring that an IM-OFDM ISAC system outperforms its OFDM ISAC counterpart for both communication and sensing. …”
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Brain Tumor Detection and Classification Using IFF-FLICM Segmentation and Optimized ELM Model by Suvashisa Dash, Mohammed Siddique, Satyasis Mishra, Demissie J. Gelmecha, Sunita Satapathy, Davinder Singh Rathee, Ram Sewak Singh

“…The IFF-FLICM algorithm is utilized to accurately segment the brain’s magnetic resonance (MR) images to identify the tumor regions. …”
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SensorDBSCAN: Semi-Supervised Active Learning Powered Method for Anomaly Detection and Diagnosis by Petr Ivanov, Maria Shtark, Alexander Kozhevnikov, Maksim Golyadkin, Dmitry Botov, Ilya Makarov

“…The proposed approach combines a transformer-based encoder trained with a triplet-based contrastive learning objective and the classical density-based clustering algorithm DBSCAN, enabling strong feature extraction, efficient and interpretable feature space organization and simple clustering algorithm. …”
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Meso-Complexity Computer Simulation Investigation on Antiexplosion Performance of Double-Layer Foam Aluminum under Pore Grading by Zhen Wang, Wen Bin Gu, Xing Bo Xie, Yu Tian Chen, Lei Fu

“…Based on the Voronoi algorithm, a three-dimensional foam aluminum generation algorithm with random pore size and random wall thickness was written by using the Python language and Fortran language. …”
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Detection of Burned Areas by Remote Sensing Techniques: İzmir Seferihisar Forest fire case study by Aslı Sabuncu, Haluk Özener

“…In addition, remote sensing techniques and algorithms are frequently used in determining the burning areas considering the long duration and the cost will be high. …”
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Cluster analysis of digital competencies among professors in higher education by Karime Chahuán-Jiménez, Eduardo Lara-Yergues, Dominique Garrido-Araya, Elena Salum-Alvarado, Paulina Hurtado-Arenas, Rolando Rubilar-Torrealba

“…Regarding the clustering analysis, specifically using the K-means clustering algorithm, four distinct clusters are identified based on the questionnaire scores, aligning with findings from Silhouette score and Quadratic error by number of clusters.DiscussionThis research reveals that professors in higher education span all four levels of competency as defined by the DigComEdu model, primarily falling within the intermediate levels of digital competencies. …”
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A Multistage Detection Framework Based on TFA and Multiframe Correlation for HFSWR by Zongtai Li, Gangsheng Li, Ling Zhang, Lanjun Liu, Q. M. Jonathan Wu

“…This study introduces an improved time-frequency analysis (TFA) algorithm to enhance the features in single-frame detection. …”
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Intelligent Turning Tool Monitoring with Neural Network Adaptive Learning by Maohua Du, Peixin Wang, Junhua Wang, Zheng Cheng, Shensong Wang

“…., (a) through distinctively designed experimental technique with comprehensive consideration of cutting parameters and tool wear values as variables, (b) through bisensor fusion for simultaneous measurements of low and high frequency signals, (c) through multitheory fusion of wavelet decomposition and the Relief-F algorithm for performing dual feature extraction and feature dimension reduction to achieve more accurate state identification using neural network, and (d) through an innovative programming technique of MATLAB-nested labVIEW. …”
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Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors by Shuangyang Mo, Cheng Huang, Yingwei Wang, Shanyu Qin

“…Subsequently, the dimensionality of these radiomics features was reduced using the least absolute shrinkage and selection operator (LASSO) algorithm. A machine learning algorithm, namely multilayer perception (MLP), was employed to construct prediction models using only the nonzero coefficient features and retained clinical features, respectively. …”
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