Optimized Prediction of Weapon Effectiveness in BVR Air Combat Scenarios Using Enhanced Regression Models by Andre R. Kuroswiski, Annie S. Wu, Angelo Passaro

“…For instance, Lasso regression, a PR method with regularization, achieves results that are 33% better and 2.1 times faster than the best artificial neural network-based solution. Our results challenge common assumptions in the literature about the complexity and feasibility of higher-order PR solutions, suggesting that they can be a compelling alternative for various challenges across domains. …”
Get full text

Study on the Detection of Dairy Cows’ Self-Protective Behaviors Based on Vision Analysis by Jia Li, Pei Wu, Feilong Kang, Lina Zhang, Chuanzhong Xuan

“…The detection algorithm is used to calculate the number of tail, leg, and head movements by using an artificial neural network. The accuracy range of the tail and head reached [0.88, 1] and the recall rate was [0.87, 1]. …”
Get full text

A decision support system based on classification algorithms for the diagnosis of periodontal disease by Abdulrahman Alshehri, Mohammed Dahman, Mousa Assiri, Abdulkarim Alshehri, Sharifah Alqahtani, Mohammed Shaiban, Bashyer Alqahtani, Sabah Althbyani, Hatem Alhefdi, Khalid Hakami, Abdulbari Ali, Abdullah Saeed

“…Aims: The purpose of this study was to develop and evaluate a decision support system (DSS) based on selected classification algorithms, namely random forest (RF), support vector machine (SVM), artificial neural network (ANN), and logistic regression for the periodontal disease diagnosis. …”
Get full text

Load frequency control in renewable based micro grid with Deep Neural Network based controller by Prasantini Samal, Niranjan Nayak, Anshuman Satapathy, Sujit Kumar Bhuyan

“…This paper introduces a novel control strategy to optimise the load frequency model in a microgrid (MG) with vehicle-to-grid interactions using Particle Swarm Optimisation - deep Artificial Neural Network (PSO-DNN). The performance of the suggested controller is evaluated against traditional techniques, including dynamic EV charging and discharging, renewable energy integration, and fluctuating generation, using the proportional integral derivative (PID) controller and the PSO-PID controller. …”
Get full text

Review on operation control of cold thermal energy storage in cooling systems by Huan Wang, Baoshan Xie, Chuanchang Li

“…Two types of cold load predictions, parametric regression and artificial neural network method, are introduced. Three aspects of economic costs are summarized in terms of initial equipment investment cost, operational cost, and life-cycle cost are summarized. …”
Get full text

ESTIMATED ELECTRICITY BILLING SYSTEM AND ITS EFFECTS ON CONSUMERS IN RESIDENTIAL AND BUSINESS CENTRES IN WUKARI METROPOLIS, TARABA STATE by Abubakar Ahmadu, Vyonkhen Tanko Nacho

“…It is recommended among others the adoption of Artificial Neural Network (ANN) to gauge consumers’ energy consumption pending the provision of prepaid meters and that National Electricity Regulatory Commission (NERC) should intensify efforts in the provision of free and/or subsidized prepaid meters to consumers. …”
Get full text

Children Tracking System Based on ZigBee Wireless Network and Neural Network by Nadia Ahmed, Sadik Kamel Gharghan, Ammar Hussein Mutlag, M. G. M. Abdolrasol

“…This paper proposes an indoor localization system based on ZigBee wireless sensor network (WSN) and Backpropagation Artificial Neural Network (BP-ANN) to locate the child in an indoor environment. …”
Get full text

An Improved Deep Learning-Based Technique for Driver Detection and Driver Assistance in Electric Vehicles with Better Performance by Gunapriya Balan, Singaravelan Arumugam, Suresh Muthusamy, Hitesh Panchal, Hossam Kotb, Mohit Bajaj, Sherif S. M. Ghoneim, null Kitmo

“…The proposed model (RF-DNN) achieved 97.05% of accuracy and the PCA-DNN model achieved 95.55% of accuracy, whereas the artificial neural network as ANN with PCA and RF achieved nearly 92% of accuracy.…”
Get full text

Implementing an Outgoing Longwave Radiation Climate Dataset from Fengyun 3E Satellite Data with a Machine-Learning Algorithm by Yanjiao Wang, Feng Yan

“…We designed a new correction model, “DeepFM”, implementing both a factorization machine algorithm and a deep artificial neural network to minimize daily mean differences between the datasets. …”
Get full text

A Hybrid Neuro-Fuzzy and Feature Reduction Model for Classification by Himansu Das, Bighnaraj Naik, H. S. Behera

“…It helps to deal with the uncertainty issues and assists the Artificial Neural Network- (ANN-) based model to achieve better performance. …”
Get full text

Forward model emulator for atmospheric radiative transfer using Gaussian processes and cross validation by O. Lamminpää, J. Susiluoto, J. Hobbs, J. McDuffie, A. Braverman, H. Owhadi

“…In contrast with artificial neural network (ANN)-based methods, it is interpretable, and its efficiency is based on learning a kernel in an engineered and expressive family of kernels.…”
Get full text

High-integrated photonic tensor core utilizing high-dimensional lightwave and microwave multidomain multiplexing by Xiangyan Meng, Nuannuan Shi, Guojie Zhang, Junshen Li, Ye Jin, Shiyou Sun, Yichen Shen, Wei Li, Ninghua Zhu, Ming Li

“…Abstract The burgeoning volume of parameters in artificial neural network models has posed substantial challenges to conventional tensor computing hardware. …”
Get full text

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. …”
Get full text

RSM-, ANN-, and GA-Based Process Optimization for Acid Centrifugation Treatment of Cane Molasses Toward Mitigating Calcium Oxide Fouling in Ethanol Plant Heat Exchanger by Lata Deso Abo, Sintayehu Mekuria Hailegiorgis, Mani Jayakumar, Sundramurthy Venkatesa Prabhu, Gadissa Tokuma Gindaba, Abas Siraj Hamda, B. S. Naveen Prasad

“…Furthermore, the implementation of an artificial neural network (ANN) provided a better prediction model for CaO reduction, with a substantial R-squared value of 0.99866. …”
Get full text

Optimizing hypertension prediction using ensemble learning approaches. by Isteaq Kabir Sifat, Md Kaderi Kibria

“…Five machine learning (ML) models such as logistic regression (LR), artificial neural network (ANN), random forest (RF), extreme gradient boosting (XGB), light gradient boosting machine (LGBM), and a stacking ensemble model were trained using selected features to predict HTN. …”
Get full text

The effect of climatic variables on vegetation indices (Case study: Orange orchards in Hassan Abad, Darab County by ALI hashemi, Hojjatollah Yazdanpanah, Mehdi Momeni

“…To determine the significance of each independent variable in predicting the dependent variables, the artificial neural network method was employed. The findings showed that the climatic elements of precipitation, minimum temperature, maximum temperature, minimum humidity, and maximum humidity had the greatest effect on EVI, with values of 0.39, 0.3, 0.13, 0.1, and 0.06 respectively. …”
Get full text

Optimal Learning Behavior Prediction System Based on Cognitive Style Using Adaptive Optimization-Based Neural Network by Ghada Aldabbagh, Daniyal M. Alghazzawi, Syed Hamid Hasan, Mohammed Alhaddad, Areej Malibari, Li Cheng

“…The learning behavior and browsing behavior features are extracted and incorporated into the input of artificial neural network (ANN). Hence, in this paper, the neural network weights are optimized with the use of grey wolf optimizer (GWO) algorithm. …”
Get full text

The Eclipsing Binaries via Artificial Intelligence. II. Need for Speed in PHOEBE Forward Models by Marcin Wrona, Andrej Prša

“…To address this, we present a fully connected feedforward artificial neural network (ANN) trained on a data set of over one million synthetic light curves generated with PHOEBE. …”
Get full text

Advanced in Islanding Detection and Fault Classification for Grid-Connected Distributed Generation using Deep Learning Neural Network by Rusvaira Qatrunnada, Novizon Novizon, Mardini Hasanah, Tuti Angraini, Anton Anton

“…The use of an Artificial Neural Network (ANN) based on the learning vector quantization (LVQ) technique is proposed in this paper for fault classification and islanding detection in grid-connected distributed generators. …”
Get full text

Rapid qualitative and quantitative analysis of strong aroma base liquor based on SPME-MS combined with chemometrics by Zongbao Sun, Junkui Li, Jianfeng Wu, Xiaobo Zou, Chi-Tang Ho, Liming Liang, Xiaojing Yan, Xuan Zhou

“…Results showed that SPME-MS combined with a back-propagation artificial neural network (BPANN) method yielded almost the same recognition performance compared to linear discriminant analysis (LDA) in distinguishing different grades of SABL, with 84% recognition rate for the test set. …”
Get full text