Simulation and explanatory analysis of dissolved oxygen dynamics in Lake Ulansuhai, China by Fan Zhang, Xiaohong Shi, Shengnan Zhao, Ruonan Hao, Biao Sun, Guohua Li, Shihuan Wang, Hao Zhang

“…Study focus: After implementing the optimal noise reduction strategies based on wavelet transform for the high-frequency monitoring data, hybrid models coupling random forests, support vector machines, and artificial neural networks were employed to simulate the dissolved oxygen in the lake during both the open-water and ice-covered periods. …”
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Effect of phosphorus fractions on benthic chlorophyll-a: Insight from the machine learning models by Yuting Wang, Sangar Khan, Zongwei Lin, Xinxin Qi, Kamel M. Eltohamy, Collins Oduro, Chao Gao, Paul J. Milham, Naicheng Wu

“…To address this gap, we applied two machine learning algorithms—random forest (RF), and artificial neural networks (ANN) to predict benthic chl-a concentrations by incorporating these specific P fractions as separate variables. …”
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A Data-Driven Deep Learning Framework for Prediction of Traffic Crashes at Road Intersections by Mengxiang Wang, Wang-Chien Lee, Na Liu, Qiang Fu, Fujun Wan, Ge Yu

“…Owing to recent advances in artificial neural networks, several new deep-learning models have been proposed for TCP. …”
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Mapping knowledge landscapes and emerging trends in artificial intelligence for antimicrobial resistance: bibliometric and visualization analysis by Zhongli Wang, Zhongli Wang, Gaopei Zhu, Shixue Li, Shixue Li

“…Keyword analysis identified six enduring research clusters from 2014 to 2024: sepsis, artificial neural networks, antimicrobial resistance, antimicrobial peptides, drug repurposing, and molecular docking, demonstrating the sustained integration of AI in antimicrobial therapy development. …”
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PlaceField2BVec: A bionic geospatial location encoding method for hierarchical temporal memory model by Zugang Chen, Shaohua Wang, Kai Wu, Guoqing Li, Jing Li, Jian Wang

“…At last, our method was compared with existing Space2BVec and Buffer2BVec in terms of location prediction accuracy and to demonstrate the robustness of the binary vector encoding methods, two brain-inspired artificial neural networks— HTM and BinaryLSTM were used. The result showed that, for HTM, in smaller geospatial space the PlaceField2BVec and Buffer2BVec had about the same accuracy on average but the highest accuracy of PlaceField2BVec is 100 %; when the geospatial space extended, our method had the highest accuracy and the average accuracy of PlaceField2BVec, Space2BVec, and Buffer2BVec is 83.9 %, 25.2 % and 69.7 % after 20 times’ training. …”
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A novel early stage drip irrigation system cost estimation model based on management and environmental variables by Masoud Pourgholam-Amiji, Khaled Ahmadaali, Abdolmajid Liaghat

“…Then, different machine learning models such as Multivariate Linear Regression, Support Vector Regression, Artificial Neural Networks, Gene Expression Programming, Genetic Algorithms, Deep Learning, and Decision Trees, were used to estimate the costs of each of the of the aforementioned sections. …”
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Comprehensive Evaluation and Error-Component Analysis of Four Satellite-Based Precipitation Estimates against Gauged Rainfall over Mainland China by Guanghua Wei, Haishen Lü, Wade T. Crow, Yonghua Zhu, Jianbin Su, Li Ren

“…Moreover, V06C and V06UC rainfall estimates are compared against the Precipitation Estimation from Remotely Sensed Imagery using Artificial Neural Networks (PERSIANN)-Climate Data Record (CDR) and the Climate Prediction Center morphing technique (CMORPH) gauge-satellite blended (BLD) products. …”
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Neural Network and Hybrid Methods in Aircraft Modeling, Identification, and Control Problems by Gaurav Dhiman, Andrew Yu. Tiumentsev, Yury V. Tiumentsev

“…We propose an approach to solving the above-mentioned problems based on artificial neural networks (ANNs) and hybrid technologies. In the class of traditional neural network technologies, we use recurrent neural networks of the NARX type, which allow us to obtain black-box models for controlled dynamical systems. …”
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Machine learning for predicting severe dengue in Puerto Rico by Zachary J. Madewell, Dania M. Rodriguez, Maile B. Thayer, Vanessa Rivera-Amill, Gabriela Paz-Bailey, Laura E. Adams, Joshua M. Wong

“…Nine ML models, including Decision Trees, K-Nearest Neighbors, Naïve Bayes, Support Vector Machines, Artificial Neural Networks, AdaBoost, CatBoost, LightGBM, and XGBoost, were trained using fivefold cross-validation and evaluated with area under the receiver operating characteristic curve (AUC-ROC), sensitivity, and specificity. …”
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Investigating factors affecting the financial recovery of businesses admitted to the stock exchange by Fatemeh Sahraei, Jafar Jamali, Hamidreza Vakilifard, Ali Zare, Seyed Yaghoub Zeraatkish

“…The findings of the Ramalho, Diogo Miguel Pacífico (2021), Kazemzadeh & Moazami (2019), and Dzingirai & Baporikar (2022) also identified and introduced factors for the revival of companies in line with the results of this research. The artificial neural network composed of the main components in this research can correctly predict 90.9% of the bankruptcy or non-bankruptcy situations of companies, which can be confirmed by the research results of Lee (2021), Barzegar & Haedari (2017), and Wanita & Grace (2021) based on the acceptable and high power of the artificial neural network in the detection of aligned bankruptcy. …”
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Designing a Model for Brand Engagement Value Creation through the Integration of Gamification Technology and Explainable Artificial Intelligence (XAI) by Zahra. Atf, fariz taherikia, kambiz heidarzadeh Hanzaei

“…The findings of the Ramalho, Diogo Miguel Pacífico (2021), Kazemzadeh & Moazami (2019), and Dzingirai & Baporikar (2022) also identified and introduced factors for the revival of companies in line with the results of this research. The artificial neural network composed of the main components in this research can correctly predict 90.9% of the bankruptcy or non-bankruptcy situations of companies, which can be confirmed by the research results of Lee (2021), Barzegar & Haedari (2017), and Wanita & Grace (2021) based on the acceptable and high power of the artificial neural network in the detection of aligned bankruptcy. …”
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In situ real-time measurement for electron spin polarization in atomic spin gyroscopes by Feng Li, Haoying Pang, Zhuo Wang, Wenfeng Fan, Min Zhang, Zehua Liu, Jiahang Li, Bodong Qin, Xinxiu Zhou, Xusheng Lei, Ruigang Wang

“…By utilizing artificial neural networks, we derive an output equation for electron spin polarization, using transmitted laser power and cell temperature as independent variables. …”
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Analysis of drought and extreme precipitation events in Thailand: trends, climate modeling, and implications for climate change adaptation by José Francisco de Oliveira-Júnior, David Mendes, Helder Dutra Porto, Kelvy Rosalvo Alencar Cardoso, José Augusto Ferreira Neto, Emannuel Bezerra Cavalcante da Silva, Marlúcia de Aquino Pereira, Monica Cristina Damião Mendes, Bernardo Bruno Dias Baracho, Punyawi Jamjareegulgarn

“…The climate indices used were Consecutive Dry Days (CDD), Maximum Number of Consecutive Summer Days (CSU), Consecutive Wet Days (CWD), Warm Spell Duration Index (WSDI), and Maximum Number of Consecutive Wet Days (WW) derived from simulations of an ensemble composed of six models from the Intergovernmental Panel on Climate Change (IPCC) via the Coupled Model Intercomparison Project Phase 6 (CMIP6) using Artificial Neural Networks (ANN) with the backpropagation method. …”
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LoCS-Net: Localizing convolutional spiking neural network for fast visual place recognition by Ugur Akcal, Ugur Akcal, Ugur Akcal, Ivan Georgiev Raikov, Ekaterina Dmitrievna Gribkova, Ekaterina Dmitrievna Gribkova, Anwesa Choudhuri, Anwesa Choudhuri, Seung Hyun Kim, Mattia Gazzola, Rhanor Gillette, Rhanor Gillette, Ivan Soltesz, Girish Chowdhary, Girish Chowdhary, Girish Chowdhary

“…Despite promising demonstrations, many state-of-the-art (SOTA) VPR approaches based on artificial neural networks (ANNs) suffer from computational inefficiency. …”
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Multi-thermal recovery layout for a sustainable power and cooling production by biomass-based multi-generation system: Techno-economic-environmental analysis and ANN-GA optimizatio... by Ma Zihao, Naeim Farouk, Pradeep Kumar Singh, Azher M. Abed, Sarminah Samad, Samah G. Babiker, Iskandar Shernazarov, Ahmed Hendy, Ahmad Almadhor, Belgacem Bouallegue, Abdul Rahman Afzal

“…A novel approach combining artificial neural networks (ANN) with a non-dominated sorting genetic algorithm II (NSGA-II) has been developed to optimize the system, substantially reducing computational time and costs associated with system performance analysis. …”
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Early prediction of long COVID-19 syndrome persistence at 12 months after hospitalisation: a prospective observational study from Ukraine by Dmytro Chumachenko, Tetyana Chumachenko, Oleksii Honchar, Tetiana Ashcheulova

“…Logistic regression and machine learning-based binary classification models have been developed to predict the persistence of LCS symptoms at 12 months after discharge.Conclusions Compared with post-COVID-19 patients who have completely recovered by 12 months after hospital discharge, those who have subsequently developed ‘very long’ COVID were characterised by a variety of more pronounced residual predischarge abnormalities that had mostly subsided by 1 month, except for steady differences in the physical symptoms levels. A simple artificial neural networks-based binary classification model using peak ESR, creatinine, ALT and weight loss during the acute phase, predischarge 6-minute walk distance and complex survey-based symptoms assessment as inputs has shown a 92% accuracy with an area under receiver-operator characteristic curve 0.931 in prediction of LCS symptoms persistence at 12 months.…”
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Designing the strategic model of online banking relational marketing in the fourth industrial revolution with the foundation's data approach. by Aliasghar Atarodi, arezo ahmadi danyali, nader gharib nawaz

“…Mohammadi fateh et al, (2022) showed that the technologies of the fourth industrial revolution are big data, biological identification system, fraud detection technologies, contactless ATM, data mining, cloud computing, marketing, versatile channel, artificial intelligence, fintech, biometrics, blockchain, intelligent social networks, artificial neural networks, remote monitoring technologies, commercial Internet of Things, and digital account, respectively. …”
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A Comprehensive Analysis of Supervised Learning Techniques for Electricity Theft Detection by Farah Aqilah Bohani, Azizah Suliman, Mulyana Saripuddin, Sera Syarmila Sameon, Nur Shakirah Md Salleh, Surizal Nazeri

“…In this paper, comparisons based on predictive accuracy, recall, precision, AUC, and F1-score of several supervised learning methods such as decision tree (DT), artificial neural network (ANN), deep artificial neural network (DANN), and AdaBoost are presented and their performances are analyzed. …”
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Machine learning and AI for advancing Parkinson's disease diagnosis: exploring promising applications by Shohreh Abdollahi, Ramin Safa

“…The analysis reveals that Artificial Neural Network achieves the highest accuracy of 92.4%, surpassing Logistic Regression and Support Vector Machine. …”
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Prediction of the Wall Factor of Arbitrary Particle Settling through Various Fluid Media in a Cylindrical Tube Using Artificial Intelligence by Mingzhong Li, Guodong Zhang, Jianquan Xue, Yanchao Li, Shukai Tang

“…Considering the influence of particle shape and the rheological properties of fluid, two artificial intelligence methods (Artificial Neural Network and Support Vector Machine) were used to predict the wall factor which is widely introduced to deduce the net hydrodynamic drag force of confining boundaries on settling particles. 513 data points were culled from the experimental data of previous studies, which were divided into training set and test set. …”
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