Forecasting energy production of a PV system connected by using NARX neural network model by Marwa M. Ibrahim, Amr A. Elfeky, Amal El Berry

“…Applying artificial neural network techniques to forecast the electricity production of photovoltaic (PV) power plants is a novel concept. …”
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The application of expert system to exploration of the robot motion by Olegas Ramašauskas, Artūras Bielskis

“…The coherency using XPS principles with artificial neural networking methods also discussed. The software implementation in Visual LISP environment examples and knowledge base files are presented. …”
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Adaptive and Resilient Flight Control System for a Small Unmanned Aerial System by Gonzalo Garcia, Shahriar Keshmiri

“…The real-time artificial neural network parameter identification is done using the sliding mode learning concept and a modified version of the self-adaptive Levenberg algorithm. …”
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Adaptive Gain Scheduled Semiactive Vibration Control Using a Neural Network by Kazuhiko Hiramoto, Taichi Matsuoka, Katsuaki Sunakoda

“…We propose an adaptive gain scheduled semiactive control method using an artificial neural network for structural systems subject to earthquake disturbance. …”
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Short-term prediction of trimaran load based on data driven technology by Haoyun Tang, Rui Zhu, Qian Wan, Deyuan Ren

“…The impact analysis on the factors such as input length, neuron number, artificial neural network (ANN) optimizer, and output scope, are taken. …”
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Federated Learning-Based Load Forecasting for Energy Aggregation Service Providers by HUANG Yichuan, SONG Yuhui, JING Zhaoxia

“…Subsequently，a weighted-average strategy was used to jointly train the artificial neural network，bridging the gap between individual energy entities and environmental features. …”
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EM Wave-Based Hand Gesture Recognition for Astronauts Using 3D Memristive Neural Network by Shilpa Pavithran, Sruthi Pallathuvalappil, Elizabeth George, Javed G S, Alex James

“…Four hand gestures are performed and classified using a three-dimensional memristive Artificial Neural Network (3D-ANN) based on Skywater 130 nm PDK (SKY130) for the ON-body to OFF-body scenario with an accuracy of 80%. …”
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A PLS-SEM Neural Network Approach for Understanding Cryptocurrency Adoption by Osama Sohaib, Walayat Hussain, Muhammad Asif, Muhammad Ahmad, Manuel Mazzara

“…The primary purpose of the study is to enhance the new technology acceptance based research with the Artificial Neural Network (ANN) method to enable more precise and in-depth research results as compared to the single-step SEM method. …”
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Neural Networks in Mechanical System Simulation, Identification, and Assessment by Thomas L. Paez

“…Artificial neural networks (ANNs) have been used in the solution of a variety of mechanical system design, analysis, and control problems. …”
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Classification of Myopathy and Amyotrophic Lateral Sclerosis Electromyograms Using Bat Algorithm and Deep Neural Networks by A. Bakiya, A. Anitha, T. Sridevi, K. Kamalanand

“…Correspondingly, the developed conventional single layer artificial neural network (neurons=7) with time domain features has shown an accuracy of 83.3%, sensitivity of 100%, and specificity of 71.42%. …”
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Vector semantic computing method study for short sentence by Fu CHEN, Chuang LIN, Chao XUE, Yue-mei XU, Kun MENG, Yi-han NI

“…A vector semantic computing method study for short sentence based on artificial neural network was proposed. And a semantic computational algorithm for social network texts as well as a discovery algorithm for mergencies was provided with reference to the information provided by the social nodes itself and the semantic of the text. …”
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Analysis of the Strategic Emission-Based Energy Policies of Developing and Developed Economies with Twin Prediction Model by Yulian Jiang, Wuchang Wei, Ramesh Chandra Das, Tonmoy Chatterjee

“…One is the Box–Jenkins method, where linear nature of the two variables is considered and the other is artificial neural network methods where nonlinear nature of the variables is also considered. …”
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Robust Prediction of Healthcare Inflation Rate With Statistical and AI Methods in Iran by Mohammad Javad Shaibani, Ali Akbar Fazaeli

“…In the next process, by doubling the forecasting window, it is observed that artificial neural network (ANN) (i.e., Bayesian NARANN) strictly outperformed other models. …”
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Application of Extreme Gradient Boosting Based on Grey Relation Analysis for Prediction of Compressive Strength of Concrete by Liyun Cui, Peiyuan Chen, Liang Wang, Jin Li, Hao Ling

“…Another highlight is that its performance was compared with the frequently used artificial neural network (ANN) and genetic algorithm-artificial neural network (GA-ANN) by using random dataset and the same testing datasets. …”
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Application of Chaos and Neural Network in Power Load Forecasting by Li Li, Liu Chong-xin

“…Delay time and embedding dimension are calculated to reconstruct the phase space and determine the structure of artificial neural network (ANN). Improved back propagation (BP) algorithm based on genetic algorithm (GA) is used to train and forecast. …”
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Design and application of electrocardiograph diagnosis system based on multifractal theory by Chun-kai ZHANG, Ao,ZHANGJing-wang YIN, Pan-bo TIAN, Ying ZHOU, Chang-qing QI

“…An automatic segmentation algorithm for ECG data using differential threshold method was designed,which could identify the various ECG cycles of continuous ECG data.And it could obtain the multifractal features of multiple fractal and generalize hurst index feature of ECG data,these features were used to train artificial neural network in order to classify ECG data,the accuracy of the classifier could reach 97%.An ECG diagnosis system was implemented,which can automatically identify ECG sequences that contain multiple ECG cycles,and can automatically ignore the incomplete ECG cycle data,and could annotate every cycle of ECG data.…”
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Optimization of Solar Panel Deployment Using Machine Learning by Shoaib Kamal, P. S. Ramapraba, Avinash Kumar, Bikash Chandra Saha, M. Lakshminarayana, S. Sanal Kumar, Anitha Gopalan, Kuma Gowwomsa Erko

“…The study takes into concern several topologies that includes series parallel topology, parallel topology, bridge link topology, honeycomb topology, and total cross tied. The artificial neural network-based topology reconfiguration strategy allows for optimal working conditions for PV arrays. …”
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Machine learning-based analyses of contributing factors for the development of hypertension: a comparative study by Marenao Tanaka, Yukinori Akiyama, Kazuma Mori, Itaru Hosaka, Keisuke Endo, Toshifumi Ogawa, Tatsuya Sato, Toru Suzuki, Toshiyuki Yano, Hirofumi Ohnishi, Nagisa Hanawa, Masato Furuhashi

“…The AUCs of ML models were 0.765–0.825, and discriminatory capacity was significantly improved in the artificial neural network model compared to that in the logistic regression model.Conclusions The development of hypertension can be simply and accurately predicted by each ML model using systolic blood pressure, age and FLI as selected features. …”
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Evaluation of sustainable energy use in sugarcane production: A holistic model from planting to harvest and life cycle assessment by Molood Behnia, Mohammad Ghahderijani, Ali Kaab, Marjan Behnia

“…The analysis compares Artificial Neural Network and Adaptive Neuro-Fuzzy Inference Systems models for predicting energy outputs and environmental effects. …”
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An emotional neural network based approach for wind power prediction by Guoling ZHANG

“…The results demonstrate that, compared with artificial neural network, ENN can improve the accuracy and reliability of the forecast by 3.8% and 46% respectively.…”
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