Sizing Control and Hardware Implementation of a Hybrid Wind-Solar Power System, Based on an ANN Approach, for Pumping Water by Ons Zarrad, Mohamed Ali Hajjaji, Aymen Jemaa, Mohamed Nejib Mansouri

“…The first contribution of our work is the utilization of an artificial neural network controller to command, at fixed atmospheric conditions, the maximum power point. …”
Get full text

Predicting the Adsorption Efficiency Using Machine Learning Framework on a Carbon-Activated Nanomaterial by Kalapala Prasad, V. Ravi Kumar, R. Suresh Kumar, A. S. Rajesh, Anjani Kumar Rai, Essam A. Al-Ammar, Saikh Mohammad Wabaidur, Amjad Iqbal, Dawit Kefyalew

“…The present study implements that the effectiveness of PCM adsorption on a carbon-activated nanomaterial was predicted using an artificial neural network, a machine learning technology. As a factor of adsorbent particle size, adsorbent dosage, training time, and starting concentrations, the adsorption capacity for each medicinal ingredient was examined. …”
Get full text

An Approach to Integrating Tactical Decision-Making in Industrial Maintenance Balance Scorecards Using Principal Components Analysis and Machine Learning by Néstor Rodríguez-Padial, Marta Marín, Rosario Domingo

“…In the proposed Custom Balance Scorecard design, an exploratory data phase is integrated with another analysis and prediction phase using Principal Component Analysis algorithms and Machine Learning that uses Artificial Neural Network algorithms. This new extension allows better control over the maintenance function of an industrial plant in the medium-term with a yearly horizon taken over monthly intervals which allows the measurement of the indicators of strategic productive areas and the discovery of hidden behavior patterns in work orders. …”
Get full text

Prediction Model of Corrosion Current Density Induced by Stray Current Based on QPSO-Driven Neural Network by Chengtao Wang, Wei Li, Gaifang Xin, Yuqiao Wang, Shaoyi Xu

“…The QPSO algorithm was employed to optimize the updating process of weights and biases in the artificial neural network (ANN). The results show that the accuracy of the proposed QPSO-NN model is better than the model based on backpropagation neural network (BPNN) and particle swarm optimization-neural network (PSO-NN). …”
Get full text

Prediction of Gas Chromatography-Mass Spectrometry Retention Times of Pesticide Residues by Chemometrics Methods by Elaheh Konoz, Amir H. M. Sarrafi, Alireza Feizbakhsh, Zahra Dashtbozorgi

“…A 6-7-1 back propagation artificial neural network (ANN) was used to improve the accuracy of the constructed model. …”
Get full text

Image-Based Face Recognition Techniques Used in Disease Detection Approaches: A Survey by Ghalib Ahmed Salman, Inas Jawad Kadhim, Ahmed Husham Al-Badri

“…FR applications relying on Artificial Neural Network (ANN) techniques have recorded higher accuracy rates in diagnosing facial diseases. …”
Get full text

Monitoring and Simulation of Dynamic Spatiotemporal Land Use/Cover Changes by Andong Guo, Yuqing Zhang, Qing Hao

“…In this study, we preprocessed multiperiod land use and socioeconomic data, combined with spatial zoning, multilayer perception (MLP) artificial neural network, and Markov chain (MC), to construct a cellular automaton model of spatial zoning. …”
Get full text

Evaluation of Contemporary Computational Techniques to Optimize Adsorption Process for Simultaneous Removal of COD and TOC in Wastewater by Areej Alhothali, Hifsa Khurshid, Muhammad Raza Ul Mustafa, Kawthar Mostafa Moria, Umer Rashid, Omaimah Omar Bamasag

“…This study was aimed at evaluating the artificial neural network (ANN), genetic algorithm (GA), adaptive neurofuzzy interference (ANFIS), and the response surface methodology (RSM) approaches for modeling and optimizing the simultaneous adsorptive removal of chemical oxygen demand (COD) and total organic carbon (TOC) in produced water (PW) using tea waste biochar (TWBC). …”
Get full text

Optimization of Mix Proportions for Novel Dry Stack Interlocking Concrete Blocks Using ANN by Krishna Prakash A, Jane Helena H, Paul Oluwaseun Awoyera

“…This paper proposes novel concrete interlocking blocks made of fly ash and GGBS which are an alternative for the conventional concrete blocks. The artificial neural network (ANN) technique is used to estimate the mechanical strength of interlocking blocks and is verified with experimental investigation. …”
Get full text

A Qualitative Approach to Universal Numerical Integrators (UNIs) with Computational Application by Paulo M. Tasinaffo, Luiz A. V. Dias, Adilson M. da Cunha

“…Abstract Universal Numerical Integrators (UNIs) can be defined as the coupling of a universal approximator of functions (e.g., artificial neural network) with some conventional numerical integrator (e.g., Euler or Runge–Kutta). …”
Get full text

Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission by Sandeep Sachdeva, Maninder Singh, U. P. Singh, Ajat Shatru Arora

“…To reduce the error of load forecasting, fuzzy method has been used with Artificial Neural Network (ANN) and OFDM transmission is used to get data from outer world and send outputs to outer world accurately and quickly. …”
Get full text

Vibration Reliability Analysis of Aeroengine Rotor Based on Intelligent Neural Network Modeling Framework by Jia-Qi Liu, Yun-Wen Feng, Cheng Lu, Wei-Huang Pan, Da Teng

“…INNMF is based on the artificial neural network (ANN) algorithm through improved particle swarm optimization (PSO) algorithm and Bayesian Regularization (BR) optimization. …”
Get full text

On the Analysis and Assessment of First-Order Group Contribution Models for the Calculation of Normal Boiling Point and Critical Properties of Pure Compounds by Vanessa Villazón-León, Adrián Bonilla-Petriciolet, Juan Carlos Tapia-Picazo

“…The performance of these models was characterized and compared for several compound families using a standardized approach to determine their group contributions and parameters. An artificial neural network model was also applied and assessed to improve the estimations obtained with the best group contribution models. …”
Get full text

Single- versus Multiobjective Optimization for Evolution of Neural Controllers in Ms. Pac-Man by Tse Guan Tan, Jason Teo, Kim On Chin

“…Pac-Man agent by using artificial neural network (ANN) and multiobjective artificial evolution. …”
Get full text

A Comparison Study on Rule Extraction from Neural Network Ensembles, Boosted Shallow Trees, and SVMs by Guido Bologna, Yoichi Hayashi

“…One way to make the knowledge stored in an artificial neural network more intelligible is to extract symbolic rules. …”
Get full text

A Software Tool for Optimal Sizing of PV Systems in Malaysia by Tamer Khatib, Azah Mohamed, K. Sopian

“…The software has the capabilities of predicting the metrological variables such as solar energy, ambient temperature and wind speed using artificial neural network (ANN), optimizes the PV module/ array tilt angle, optimizes the inverter size and calculate optimal capacities of PV array, battery, wind turbine and diesel generator in hybrid PV systems. …”
Get full text

A Machine Learning-Based Model for Predicting Atmospheric Corrosion Rate of Carbon Steel by Ngoc-Long Tran, Trong-Ha Nguyen, Van-Tien Phan, Duy-Duan Nguyen

“…The purpose of this study is to develop a practical artificial neural network (ANN) model for predicting the atmospheric corrosion rate of carbon steel. …”
Get full text

A Novel Kernel for RBF Based Neural Networks by Wasim Aftab, Muhammad Moinuddin, Muhammad Shafique Shaikh

“…In this work, we introduce a novel RBF artificial neural network (ANN) where the basis function utilizes a linear combination of ED based Gaussian kernel and a cosine kernel where the cosine kernel computes the angle between feature and center vectors. …”
Get full text

Global and regional perspectives on optimizing thermo-responsive dynamic windows for energy-efficient buildings by Yuan Gao, Jacob C. Jonsson, D. Charlie Curcija, Simon Vidanovic, Tianzhen Hong

“…World heatmap results, derived from well-trained artificial neural network models, reveal that thermo-responsive windows are especially useful in climates where buildings demand both heating and cooling energy, whereas thermo-responsive windows with optimal transition temperatures show no dynamic features in most of low-latitude tropical regions. …”
Get full text

Predicting the urban water demand by equipping intelligent-based methods with discrete wavelet transform function by Mohammad Reza Alikhani, Ramtin Moeini

“…For this purpose, in this research, artificial intelligence and data mining methods, including genetic programming (GP), gene expression programming (GEP), artificial neural network (ANN), and discrete wavelet transform function, are used to predict the daily drinking water consumption values of WDN. …”
Get full text