Prediction-Based Maintenance of Existing Bridges Using Neural Network and Sensitivity Analysis by Pengyong Miao

“…This study proposed a methodology to resolve these issues by integrating an artificial neural network (ANN) and sensitivity analysis method. …”
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An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models by Dongwoo Jang

“…In this study, the precipitation of five regional climate models and actual observed precipitation provided in Korea are applied to ANN (artificial neural network), which suggests ways to improve prediction accuracy for precipitation. …”
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Flood Forecasting for Small Reservoirs Based on Neural Networks by PENG Wei, XIONG Jiayi, JIANG Xianqun, GAO Yueming

“…In flood forecasting,empirical prediction methods report low accuracy,and traditional hydrological models face the problems of large workloads and difficult promotion when they are applied to small reservoirs.Hence,an artificial neural network (ANN) method is introduced,which is equipped with powerful feature-learning capability.It is combined with the genetic algorithm (GA) to find the optimal parameters for flood forecasting of small reservoirs as GA can realize automatic optimization of the time step and hidden-layer neuron nodes in ANN.In this way,parameter search can be targeted,and personalized flood forecasting models can be constructed for each small reservoir.In addition,the flood forecasting models based on the back propagation (BP),long short-term memory (LSTM),and gated recurrent unit (GRU) neural networks are built,and comparisons between simulations and measured data are conducted for the flood process.The results show that the LSTM model has high prediction accuracy and good stability and can learn and simulate the water-level change pattern of the actual flood process,demonstrating better prediction performance than BP and GRU models.…”
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A Design Space Exploration Framework for ANN-Based Fault Detection in Hardware Systems by Andreas G. Savva, Theocharis Theocharides, Chrysostomos Nicopoulos

“…This work presents a design exploration framework for developing a high level Artificial Neural Network (ANN) for fault detection in hardware systems. …”
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A Neural-Wavelet Technique for Damage Identification in the ASCE Benchmark Structure Using Phase II Experimental Data by Mahmoud M. Reda Taha

“…We describe a robust damage detection method that is based on using artificial neural network (ANN) to compute the wavelet energy of acceleration signals acquired from the structure. …”
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Effect of Process Parameters on Short Fiber Orientation along the Melt Flow Direction in Water-Assisted Injection Molded Part by Haiying Zhou, Hesheng Liu, Qingsong Jiang, Tangqing Kuang, Zhixin Chen, Weiping Li

“…The effect of six process parameters, including filling time, melt temperature, mold temperature, delay time, water pressure, and water temperature, on the SFO along the melt flow direction were studied through orthogonal experimental design, range analysis, and variance analysis. An artificial neural network was used to establish the nonlinear agent model between the process parameters and A11 representing the fiber orientation in melt flow direction. …”
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On the Prediction of Product Aesthetic Evaluation Based on Hesitant-Fuzzy Cognition and Neural Network by Xinying Wu, Minggang Yang, Zishun Su, Xinxin Zhang

“…By measuring the cognitive complexity of the product, this research establishes the relationship between the complexity and aesthetics of the product using an artificial neural network. Hence the prediction of product beauty is achieved, which guides design decisions. …”
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Machine Learning for Ischemic Heart Disease Diagnosis Aided by Evolutionary Computing by Mohammad Alsaffar, Abdullah Alshammari, Gharbi Alshammari, Saud Aljaloud, Tariq S. Almurayziq, Fadam Muteb Abdoon, Solomon Abebaw

“…A picture database containing 92 images of electrocardiogram signals was also used in this project for the analysis of the Artificial Neural Network. After extensive research and testing by the medical community, which supported the project and provided positive feedback, a successful tool was developed. …”
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Multifractal Analysis and Compressive Strength Prediction for Concrete through Acoustic Emission Parameters by Zhiqiang Lv, Annan Jiang, Jiaxu Jin, Xiangfeng Lv

“…SVM prediction results using AE parameters perform higher precision than the artificial neural network (ANN). Furthermore, a significant reduction in sample size uses AE parameters to predict concrete strength.…”
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Specifying High‐Altitude Electrons Using Low‐Altitude LEO Systems: The SHELLS Model by S. G. Claudepierre, T. P. O'Brien

“…Abstract We describe an artificial neural network model of the near‐Earth space radiation environment. …”
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Factors Affecting Digital Financial Service Adoption in Bangladesh: Evidence from SEM-ANN Approaches by Nafis Sadik, Md. Mominur Rahman

“…This study investigates the key drivers affecting the adoption of DFS in Bangladesh by employing Structural Equation Modeling (SEM) and Artificial Neural Network (ANN) approaches. Using survey data collected from 340 DFS users, the SEM analysis validates the proposed relationships, identifying financial literacy, trust, access to capital, digital payment usage, and digital financial inclusion as significant factors driving DFS adoption. …”
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Estimating the Ultimate Bearing Capacity for Strip Footing Near and within Slopes Using AI (GP, ANN, and EPR) Techniques by Ahmed M. Ebid, Kennedy C. Onyelowe, Emmanuel E. Arinze

“…The genetic programming (GP), evolutionary polynomial regression (EPR), and artificial neural network (ANN) intelligent techniques were employed to predict the ultimate bearing capacity of footing on or adjacent to a slope. …”
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Solar Irradiance Prediction for Zaria Town Using Different Machine Learning Models by Ibrahim Abdulwahab, Sulaiman Haruna Sulaiman, Umar Musa, Ibrahim Abdullahi Shehu, Abdullahi Kakumi Musa, Ismaila Mahmud, Mohammed Musa, Abdullahi Abubakar, Abdulrahman Olaniyan

“…Four machine learning models (artificial neural network (ANN), decision tree (DT), random forest (RF), and gradient boost tree (GBT).) were used to predict and compare actual and anticipated solar radiation values. …”
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Hybrid Wind Speed Forecasting Model Study Based on SSA and Intelligent Optimized Algorithm by Wenyu Zhang, Zhongyue Su, Hongli Zhang, Yanru Zhao, Zhiyuan Zhao

“…The present study investigated singular spectrum analysis (SSA) with a reduced parameter algorithm in three time series models, the autoregressive integrated moving average (ARIMA) model, the support vector machine (SVM) model, and the artificial neural network (ANN) model, to forecast the wind speed in Shandong province, China. …”
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Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures by Niels H. Christiansen, Per Erlend Torbergsen Voie, Ole Winther, Jan Høgsberg

“…Training of an artificial neural network (ANN) adjusts the internal weights of the network in order to minimize a predefined error measure. …”
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APPLICATION OF COMPRESSIVE SENSING AND IMPROVED DEEP WAVELET NEURAL NETWORK IN BEARING FAULT DIAGNOSIS by DU XiaoLei, CHEN ZhiGang, ZHANG Nan, XU Xu

“…The feature extraction ability and recognition ability of proposed method are superior than artificial neural network,deep belief network,deep sparse auto-encoder and so on.…”
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Prediction of thermal conductivity in CALF-20 with first-principles accuracy via machine learning interatomic potentials by Soham Mandal, Prabal K. Maiti

“…Here, we report the thermal transport study of CALF-20 using artificial neural network-based machine learning potentials. …”
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Forecasting financial distress for organizational sustainability: An empirical analysis by Soumya Ranjan Sethi, Dushyant Ashok Mahadik

“…This study aims to assess the predictive capabilities of Artificial Neural Network (ANN), Logistic Regression (LR), and Linear Discriminant Analysis (LDA) in predicting a company's bankruptcy. …”
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Experimental and computational investigation of the effect of machining parameters on the turning process of C45 steel by Tien-Thinh Le, Hang Thi Pham, Hiep Khac Doan, Panagiotis G. Asteris

“…Finally, for practical purposes, an artificial neural network model based on machine learning is developed to predict the average temperature near the turning insert nose.…”
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On Modelling and Comparative Study of LMS and RLS Algorithms for Synthesis of MSA by Ahmad Kamal Hassan, Adnan Affandi

“…This paper deals with analytical modelling of microstrip patch antenna (MSA) by means of artificial neural network (ANN) using least mean square (LMS) and recursive least square (RLS) algorithms. …”
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