Discovering the Hidden Secrets in Your Data - the Data Mining Approach to Information by Michael Lloyd-Williams

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Bearing Fault Diagnosis Method based on Sensitive Component and MCPG by Mingliang Zhang, Hongkun Li, Yue Ma, Gangjin Huang, Yuchen Xu

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Operational Forecasting of Wind Speed for an Self-Contained Power Assembly of a Traction Substation by P. V. Matrenin, A. I. Khalyasmaa, A. G. Rusina, S. A. Eroshenko, N. A. Papkova, D. A. Sekatski

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Investigation of the application of an automated monitoring system for detecting transmission cable deterioration in Nigeria: A case study of transmission cable lines between Offa... by C.S. Omoniabipi, R. Agbadede, K.C. Emmanuel, O.J. Adewuni, I. Allison

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Breast Cancer Detection Using Deep Learning by ahmed Abed Maeedi, Dalal Abdulmohsin Hammood, Shatha Mezher Hasan

Subjects: “…breast cancer, deep learning, cnn, neural networks, hybrid lstm-cnn.…”
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MD-Unet for tobacco leaf disease spot segmentation based on multi-scale residual dilated convolutions by Zili Chen, Yilong Peng, Jiadong Jiao, Aiguo Wang, Laigang Wang, Wei Lin, Yan Guo

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Measurement of Total Flow Rates in Horizontal Well Oil-Water Two-Phase Flows by the Application of BP Neural Network Algorithm to Production Array Logs by Xin Zhang, Hongwei Song, Haimin Guo, Xinlei Shi

“…To obtain the total flow rate of oil-water two-phase flows in horizontal wells, in this paper, Multiple Array Production Suite (MAPS), which is also called Production Array Logs (PAL), is used to conduct simulation experiments, uses BP neural network (BPNN) algorithm to train the data samples, and establishes the prediction models of the total flow rates of oil-water two-phase flows in horizontal wells. …”
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Analysis and Optimization of the Spatial Patterns of Commercial Service Facilities Based on Multisource Spatiotemporal Data and Graph Neural Networks: A Case Study of Beijing, China by Yihang Xiao, Cunzhi Li, Zhiwu Zhou, Dongyang Hou, Xiaoguang Zhou

“…This paper utilizes multisource spatiotemporal data, employing geographic spatial analysis methods and graph neural network models to explore the spatial structure of commercial service facilities in Beijing and their relationships with population density and land use, thereby achieving a detailed classification of the commercial service patterns at the natural neighborhood scale. …”
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Using Flow 3D Simulation, Multiple Nonlinear Regression Approach, and Artificial Neural Network Approach Approaches to Study the Behavior of Vertical Drop Structures by Shaikhli Hasan Al, Mohammed Sarah Hashim, Al-Khafaji Zainab

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Use of Artificial Neural Networks and Multiple Linear Regression Model for the Prediction of Dissolved Oxygen in Rivers: Case Study of Hydrographic Basin of River Nyando, Kenya by Yashon O. Ouma, Clinton O. Okuku, Evalyne N. Njau

“…To overcome the lack of data in water quality monitoring and prediction, this paper presents an approach based on the feedforward neural network (FNN) model for the simulation and prediction of dissolved oxygen (DO) in the Nyando River basin in Kenya. …”
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Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

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Harvesting Solar Energy: Prediction of Daily Global Horizontal Irradiance Using Artificial Neural Networks and Assessment of Electrical Energy of Photovoltaic at North Eastern Ethiopia by Tegenu A. Woldegiyorgis, Abera D. Assamnew, Gezahegn A. Desalegn, Sentayehu Y. Mossie

“…Thus, the objectives of this article were: (i) assessing daily global horizontal irradiance using network types‐activation functions of artificial neural network (ANN); and (ii) evaluating the daily energy delivered to and available on photovoltaic (PV) cells of GaAs at Kemissie, Woldiya, and Hayk, in the northeastern part of Ethiopia. …”
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A Novel Design of a Neural Network-Based Fractional PID Controller for Mobile Robots Using Hybridized Fruit Fly and Particle Swarm Optimization by Ghusn Abdul Redha Ibraheem, Ahmad Taher Azar, Ibraheem Kasim Ibraheem, Amjad J. Humaidi

“…This work offers the analysis, design, and simulation of a new neural network- (NN) based nonlinear fractional control structure. …”
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Dynamical Complexity Transitions During High‐Intensity Long Duration Continuous Auroral Activities (HILDCAA) Events: Feature Analysis Based on Neural Network Entropy by I. A. Oludehinwa, A. Velichko, B. O. Ogunsua, O. I. Olusola, O. O. Odeyemi

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Development an Artificial Neural Network Model for Estimating Cost of R/C Building by Using Life-Cycle Cost Function: Case Study of Mexico City by Henry E. Reyes, Juan Bojórquez, Laura Cruz-Reyes, Sonia E. Ruiz, Alfredo Reyes-Salazar, Edén Bojórquez, Manuel Barraza, Antonio Formisano, Omar Payán, José R. Torres

“…The objective of this study is to develop an artificial neural network (ANN) model that can estimate the total expected cost of R/C buildings by using LCC functions. …”
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Modeling TEC Maps Over China Using Particle Swarm Optimization Neural Networks and Long‐Term Ground‐Based GPS, COSMIC, and Fengyun Data by Shuangshuang Shi, Kefei Zhang, Jiaqi Shi, Andong Hu, Dongsheng Zhao, Zhongchao Shi, Peng Sun, Huajing Wu, Suqin Wu

“…The PSO algorithm is used to optimize the traditional back‐propagation neural network (BP‐NN) model by reducing the effects of the local minimum problem. …”
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Brittleness evaluation of main coal seams in Permian Taiyuan-Shanxi formations, Baode block, Ordos Basin: based on a convolutional neural network method by Qingfeng ZHANG, Ziling LI, Jikun ZHANG, Shuai HAO, Xiaoguang SUN, Yanjie SHANG, Yun ZUO

Subjects: “…convolutional neural network…”
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Evaluating Neural Network Performance in Predicting Disease Status and Tissue Source of JC Polyomavirus from Patient Isolates Based on the Hypervariable Region of the Viral Genome by Aiden M. C. Pike, Saeed Amal, Melissa S. Maginnis, Michael P. Wilczek

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Traffic flow modelling of vehicles on a six lane freeway: Comparative analysis of improved group method of data handling and artificial neural network model by Isaac Oyeyemi Olayode, Alessandro Severino, Frimpong Justice Alex, Elmira Jamei

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A Low‐Latitude Three‐Dimensional Ionospheric Electron Density Model Based on Radio Occultation Data Using Artificial Neural Networks With Prior Knowledge by Ding Yang, Hanxian Fang

“…Previous ionospheric models using artificial neural networks (ANN) are only data‐driven, whose effects are entirely affected by observational data. …”
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