A comprehensive machine learning-based models for predicting mixture toxicity of azole fungicides toward algae (Auxenochlorella pyrenoidosa) by Li-Tang Qin, Xue-Fang Tian, Jun-Yao Zhang, Yan-Peng Liang, Hong-Hu Zeng, Ling-Yun Mo

“…The results indicated that models employing concentration addition (CA), independent action (IA), and molecular descriptors (MD) as variables demonstrated superior predictive abilities. The consensus model combining SVM and RF algorithms (labeled as CM0) demonstrated the highest level of accuracy in fitting the data, with a coefficient of determination of 0.980. …”
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Machine Learning and Deep Learning Models for Dengue Diagnosis Prediction: A Systematic Review by Daniel Cristobal Andrade Girón, William Joel Marín Rodriguez, Flor de María Lioo-Jordan, Jose Luis Ausejo Sánchez

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Improving the Quality of Experience of Video Streaming Through a Buffer-Based Adaptive Bitrate Algorithm and Gated Recurrent Unit-Based Network Bandwidth Prediction by Jeonghun Woo, Seungwoo Hong, Donghyun Kang, Donghyeok An

“…For improved quality of experience (QoE), streaming services utilize adaptive bitrate (ABR) algorithms to handle network bandwidth variations. ABR algorithms use network bandwidth history for future network bandwidth prediction, allowing them to perform efficiently when network bandwidth fluctuations are minor. …”
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Air quality prediction method based on improved BCCSA and deep LSTM by Wei Shiyue, Xu Hongzhen

“…Therefore, an air quality prediction method based on improved binary chaotic crow search algorithm(BCCSA) and deep long short term memory neural network(LSTM) is proposed. …”
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Machine learning-based seismic response forecasting using feature mapping algorithms and scientometric analysis of nailed vertical excavation in a soil mass by Surya Muthukumar, Dhanya Sathyan, Premjith B, Sanjay Kumar Shukla

“…The ML algorithms, RBF kernel and random Fourier features consistently delivered strong performance pairing with linear regression algorithm. …”
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Real-time prediction of port water levels based on EMD-PSO-RBFNN by Lijun Wang, Shenghao Liao, Sisi Wang, Jianchuan Yin, Ronghui Li, Jingyu Guan

Subjects: “…port water level prediction…”
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Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch by Igor Gulshin, Nikolay Makisha

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Forecasting loan, deferred rate and customer segmentation in banking industry: A computational intelligence approach by Mahtab Vasheghani, Ebrahim Nazari Farokhi, Behrooz Dolatshah

Subjects: “…Evolutionary algorithms…”
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A machine learning-based prediction of diabetic retinopathy using the Korea national health and nutrition examination survey (2008–2012, 2017–2021) by Min Seok Kim, Young Wook Choi, Borghare Shubham Prakash, Youngju Lee, Soo Lim, Se Joon Woo

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Machine Learning in the Teaching Quality of University Teachers: Systematic Review of the Literature 2014–2024 by Walter Zambrano-Romero, Ciro Rodriguez, Josselyn Pita-Valencia, Walter José Zambrano-Romero, José Manuel Moran-Tubay

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DISEÑO DE UN PICOSATÉLITE PARA EL MONITOREO Y PREDICCIÓN DEL COMPORTAMIENTO DE INCENDIOS FORESTALES by Miguel Felipe Cano Bogotá, Valeria Navarro Lizcano, Ricardo Andrés Santa Quintero

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Stochastic Characterization of Faults in Electrical Transmission Networks: Case Study of the Electrical Community of Benin by Mohamed Barate, Eyouléki Tcheyi Gnadi Palanga, Ayité Sénah Akoda Ajavon, Kodjo Agbossou

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Diagnostic accuracy of artificial intelligence algorithms to predict remove all macroscopic disease and survival rate after complete surgical cytoreduction in patients with ovarian cancer: a systematic review and meta-analysis by Somayyeh Noei Teymoordash, Hoda Zendehdel, Ali Reza Norouzi, Mahdis Kashian

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Prediction of the 180 day functional outcomes in aneurysmal subarachnoid hemorrhage using an optimized XGBoost model by Weichong Zhou, Xingfu Liao, Hui Shi, Mingfeng Wang, Yunchong Xiao, Xilu Yu, Yilong Wu, YanYi Liu, Yin Peng, Hai Su

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One-point Method for Speed Strategy Optimization Based on Slope Simplification and Speed Limit Prediction by XING Jian, HAN Bing

Subjects: “…speed limit prediction…”
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Vessel Traffic Flow Prediction in Port Waterways Based on POA-CNN-BiGRU Model by Yumiao Chang, Jianwen Ma, Long Sun, Zeqiu Ma, Yue Zhou

“…Aiming at the stage characteristics of vessel traffic in port waterways in time sequence, which leads to complexity of data in the prediction process and difficulty in adjusting the model parameters, a convolutional neural network (CNN) based on the optimization of the pelican algorithm (POA) and the combination of bi-directional gated recurrent units (BiGRUs) is proposed as a prediction model, and the POA algorithm is used to search for optimized hyper-parameters, and then the iterative optimization of the optimal parameter combinations is input into the best combination of iteratively found parameters, which is input into the CNN-BiGRU model structure for training and prediction. …”
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A Deformation Prediction Model for Concrete Dams Based on RSA-VMD-AttLSTM by Pei Liu, Hao Gu, Chongshi Gu, Yanbo Wang

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Auditing Flood Vulnerability Geo-Intelligence Workflow for Biases by Brian K. Masinde, Caroline M. Gevaert, Michael H. Nagenborg, Marc J. C. van den Homberg, Jacopo Margutti, Inez Gortzak, Jaap A. Zevenbergen

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Unveiling geological complexity in the Serra Dourada Granite using self-organizing maps and hierarchical clustering: Insights for REE prospecting in the Goiás Tin Province, Brasíli... by Guilherme Ferreira da Silva, Marcos Vinícius Ferreira, Lucy Takehara Chemale, Igor Vasconcelos Santana, Nilson Francisquini Botelho

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Siamese Graph Convolutional Split-Attention Network with NLP based Social Sentimental Data for enhanced stock price predictions by Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni

“…Finally, a Graph Convolutional Split-Attention Network (SGCSAN) for promisingly predicting whether the stock prices are going to hit the ground and fly high again or is going to nosedive with Humboldt Squid Optimization Algorithm (HSOA) is introduced to further improve accuracy with lesser error generation. …”
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