Leveraging machine learning to proactively identify phishing campaigns before they strike by Kun Zhang, Haifeng Wang, Meiyi Chen, Xianglin Chen, Long Liu, Qiang Geng, Yu Zhou

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Lightning Risk Assessment of 10 kV Distribution Line Based on TOPSIS Algorithm Improved by Weighted Mahalanobis Distance by Yan DU, Congzhen XIE, Yancheng LI, Xinhao XIE, Le LUAN, Simin LUO

“…Then TOPSIS algorithm improved by weighted Mahalanobis distance was used to build the lightning risk assessment system of 10 kV distribution network, and the risk was scaled. …”
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Numerical Modeling on Ocean-Bottom Seismograph P-Wave Receiver Function to Analyze Influences of Seawater and Sedimentary Layers by Wenfei Gong, Hao Hu, Aiguo Ruan, Xiongwei Niu, Wei Wang, Yong Tang

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Feature selection using a multi-strategy improved parrot optimization algorithm in software defect prediction by Qi Fei, Guisheng Yin, Zhian Sun

“…Comparative experiments demonstrate that BMEPO exhibits stronger competitiveness in feature selection quality and classification performance compared to advanced feature selection algorithms. Finally, to further enhance the classification performance of defect prediction, a heterogeneous data stacking ensemble learning algorithm (HEDSE) based on feature selection is proposed. …”
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Investigation of soil resistivity impacts on the electrodes of grounding system subjected to lightning strikes by Osama E. Gouda, Adel Z. El Dein, Sara Yassin, Matti Lehtonen, Mohamed M. F. Darwish

“…The field resulting from lightning strikes, which causes soil ionization, has been studied, and the results have been used to understand the behaviour of ground rods under the influence of lightning strikes. …”
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Seismic Identification and Characterization of Deep Strike-Slip Faults in the Tarim Craton Basin by Fei Tian, Wenhao Zheng, Aosai Zhao, Jingyue Liu, Yunchen Liu, Hui Zhou, Wenjing Cao

“…Our detailed evaluation encompassed 12 distinct seismic attributes, culminating in the creation of a sophisticated model for identifying strike-slip faults. This model incorporates select seismic attributes and leverages fusion algorithms like K-means, ellipsoid growth, and wavelet transformations. …”
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DeepInvesting: Stock market predictions with a sequence-oriented BiLSTM stacked model – A dataset case study of AMZN by Ashkan Safari, Mohammad Ali Badamchizadeh

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LIFO-STACK SIZE DETERMINATION FOR GROWING OF THE IMAGE REGIONS by V. Yu. Tsviatkou

“…This paper considers the problem of memory allocation for the organization of the LIFO-stack in the algorithm for image segmentation based on growing regions is considered. …”
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Using Stacks for Image Segmentation Based on Region Growing by V. Yu. Tsviatkou

“…Expressions are obtained in the paper that allow one to increase the accuracy of determining the sizes of FIFO and LIFO stacks necessary for storing the coordinates of adjacent pixels in a segmentation algorithm based on growing regions under maximum load conditions. …”
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A Multi-Objective Temperature Control Method for a Multi-Stack Fuel Cell System with Different Stacks Based on Model Predictive Control by Wei Shen, Hongtao Su, Jianhua Gao, Lei Fan, Gang Zhang, Su Zhou

“…In order to control each stack temperature in an MFCS, the model predictive control (MPC) algorithm based on the backpropagation (BP) neural network is proposed. …”
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ECG Signal Ｒecognition Based on Deep Stacked Network by ZHANG Ｒiu, WANG Ｒu, HUANG Jun, ZENG Xin

“…The traditional electrocardiogram ( ECG) signal recognition algorithms rely on ECG experts to participate in feature recognition，which is time-consuming and laborious with high diagnostic cost. …”
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An adaptive hierarchical hybrid kernel ELM optimized by aquila optimizer algorithm for bearing fault diagnosis by Hao Yan, Liangliang Shang, Wan Chen, Mengyao Jiang, Tianqi lu, Fei Li

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A Hybrid Machine Learning-Based Framework for Data Injection Attack Detection in Smart Grids Using PCA and Stacked Autoencoders by Shahid Tufail, Hasan Iqbal, Mohd Tariq, Arif I. Sarwat

“…Various machine learning algorithms were evaluated, and the Random Forest (RF) model consistently achieved superior accuracy, ranging from 99.32% to 95.89%. …”
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Experimental study on the piezoelectric active vibration reduction system of wind tunnel aerodynamic models by LI Weiguang, YANG Zhichun, ZHU Ximing

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AI-enhanced automation of building energy optimization using a hybrid stacked model and genetic algorithms: Experiments with seven machine learning techniques and a deep neural network by Mohammad H. Mehraban, Samad ME Sepasgozar, Alireza Ghomimoghadam, Behrouz Zafari

“…Unlike the common practices, the scenario development and building optimization tend to be enhanced by using AI in the present paper, using a Python-based script alongside the Non-dominated Sorting Genetic Algorithm (NSGA-II) through EnergyPlus simulations. …”
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Forecasting Blue and Green Water Footprint of Wheat Based on Single, Hybrid, and Stacking Ensemble Machine Learning Algorithms Under Diverse Agro-Climatic Conditions in Nile Delta, Egypt by Ashrakat A. Lotfy, Mohamed E. Abuarab, Eslam Farag, Bilal Derardja, Roula Khadra, Ahmed A. Abdelmoneim, Ali Mokhtar

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A Hybrid Three-Staged, Short-Term Wind-Power Prediction Method Based on SDAE-SVR Deep Learning and BA Optimization by Ruiqin Duan, Xiaosheng Peng, Cong Li, Zimin Yang, Yan Jiang, Xiufeng Li, Shuangquan Liu

Subjects: “…Stack denoising autoencoder…”
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Heuristic Optimization-Based Trajectory Planning for UAV Swarms in Urban Target Strike Operations by Chen Fei, Zhuo Lu, Weiwei Jiang

“…To address this challenge, this paper proposes a target strike strategy using the Electric Eel Foraging Optimization (EEFO) algorithm, a heuristic optimization method designed to ensure precise strikes in complex environments. …”
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Research on Damage Assessment Method for Reinforced Concrete T-Girder Bridges Under Munitions Strikes by Xi Chen, Hongbo Zhai, Qipeng Xu, Wei Wei

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Enhancing Intrusion Detection Systems with Dimensionality Reduction and Multi-Stacking Ensemble Techniques by Ali Mohammed Alsaffar, Mostafa Nouri-Baygi, Hamed Zolbanin

“…To overcome these limitations, this paper presents an innovative approach that integrates dimensionality reduction and stacking ensemble techniques. We employ the LogitBoost algorithm with XGBRegressor for feature selection, complemented by a Residual Network (ResNet) deep learning model for feature extraction. …”
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