Evaluation of the relationships between physico-chemical parameters and the abundance of Vibrio spp. in blue crabs (Callinectes sapidus) and seawater from the Maryland Coastal Bays by Jasmine Smalls, John Jacobs, Howard Townsend, Paulinus Chigbu, Salina Parveen

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Evaluating the Effectiveness of Dimensionality Reduction on Machine Learning Algorithms in Time Series Forecasting by Rida Zaheer, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Ramzan Talib

“…The effectiveness of different dimensionality reduction methods is evaluated based on their ability to simplify data while preserving essential features. …”
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The value of systemic inflammatory response index in evaluating the prognosis of postoperative patients with stage II colon cancer by Yong Wang, Longlong Ding, Lingyan Ji, Zhao Yan

“…Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of various influencing factors on postoperative prognosis of stage II colon cancer patients. …”
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Construction of a deep learning-based predictive model to evaluate the influence of mechanical stretching stimuli on MMP-2 gene expression levels in fibroblasts by Ruozu Xiao, Haowei Zhou, Zhen Shi, Rong Huang, Yuheng Zhang, Jing Li

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Application of Supervised Learning Methods and Information Gain Methods in the Determination of Asbestos–Cement Roofs’ Deterioration State by Manuel Saba, David Valdelamar Martínez, Leydy K. Torres Gil, Gabriel E. Chanchí Golondrino, Manuel A. Ospina Alarcón

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Rapid prediction of beef colour evolution and myoglobin forms using near-infrared spectroscopy (NIRS) by Wenyang Jia, Nigel Scollan, Anastasios Koidis

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Short-Term Power Prediction Method for Photovoltaic Power Plants Based on ECA-MTGNN Integration by HUANG Congzhi, LIU Yantong

“…Finally, the prediction performance of the proposed method was evaluated using the prediction accuracy assessment criteria specific to PV power plants in the northern China region and the general evaluation metrics for time series prediction. …”
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Robust Controllability Network Method on Temporal Network Using Temporal Link Prediction and Network Embedding by Yan Dou, WanLin Liu, Peyman Arebi

“…The effectiveness of the proposed method against various network attacks has been evaluated and compared with other conventional methods. …”
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Bearing Lifespan Reliability Prediction Method Based on Multiscale Feature Extraction and Dual Attention Mechanism by Xudong Luo, Minghui Wang

“…However, due to the high nonlinearity and complexity of mechanical systems, traditional methods failed to meet the requirements of medium- and long-term prediction tasks. …”
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Carbon emission prediction method of steel plants based on long short-term memory network by Fengyun LI, Zehui DOU, Peng LI, Wei GUO

“…As the second largest carbon emitter in China, iron and steel enterprises have great potential for carbon emission reduction.In order to facilitate the supervision and control of carbon emissions by relevant departments, carbon emission prediction research is carried out.Taking a steelmaking plant as the research object, firstly, the carbon dioxide emissions in the steelmaking process were analyzed, and 10 energy substances that caused carbon emissions were determined.The basic energy data of the steelmaking plant from 2001 to 2023 were collected, and the carbon emissions were calculated from the basic energy data according to the carbon emission accounting method.Secondly, based on the long short-term memory network to predict the carbon emissions in the next 7 years, the training error and test error were close to 0.01, and the actual error was 1 323 307.46 tons of carbon dioxide.Then, the Mann-Kendall trend test was used to evaluate the overall carbon emission trend of the steelmaking plant.Finally, some reasonable suggestions were put forward for steelmaking plants in order to actively respond to the goal of low-carbon environmental protection.…”
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A New Method to Predict Shock-Type Coal-Gas Outburst Disaster and Its Application by Pengfei Lyu, Tan Li, Xuehua Chen

“…The mechanism of coal-gas outbursts is complex, and the prediction methods are immature at present. This article was based on previous research results. …”
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A Ship Underwater Radiated Noise Prediction Method Based on Semi-Supervised Ensemble Learning by Xin Huang, Rongwu Xu, Ruibiao Li

“…Accurate prediction of ship underwater radiated noise (URN) during navigation is critical for evaluating acoustic stealth performance and analyzing detection risks. …”
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Hybrid regression method to predict forest variables from Earth observation data in boreal forests by Eelis Halme, Matti Mõttus

“…The prediction performance was evaluated using three independent test areas, two from Finland and one from Sweden. …”
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Random Displacement Method-based Model for Predicting the Distribution of Net Sediment Deposition in Vegetated Channels by Chuan LI, Sichen SUN, Yuqi SHAN, Yonghao LIU, Chao LIU

“…In conclusion, the proposed random displacement method-based numerical model accurately predicts the distribution of sediment deposition inside vegetated regions in open channels, provided the upstream sediment supply is not limited.…”
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A prediction method for anti-cancer drug combinations synergy based on graph attention network by QIN Weiqi;BAO Xin;CHEN Xiao;QIU Jianlong;WANG Donglin

“…It then employs a graph attention network(GAT) and multilayer perceptron(MLP) to extract features from both drug and cell line data, fusing these multi-source features to predict combination synergy. Evaluated on a public dataset, MFGSynergy outperforms Deep DDS, DeepSynergy, and six machine learning methods, achieving receiver operating characteri-stic area under the curve(ROC AUC), area under the precision-recall curve(PR AUC), accuracy(ACC), precision(PREC), true positive rate(TPR), and F1scores of 0.94, 0.94, 0.86, 0.87, 0.86, and 0.86, respectively, in five-fold cross-validation. …”
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Cropland Suitability Prediction Method Based on Biophysical Variables from Copernicus Data and Machine Learning by Dorijan Radočaj, Mateo Gašparović, Mladen Jurišić

“…The goal of this study was to propose and validate a method for predicting cropland suitability based on biophysical variables and machine learning according to an FAO land suitability standard using soybean (<i>Glycine max</i> L.) as a representative crop, aiming to provide an alternative to geographic information system (GIS)-based multicriteria analysis. …”
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Vehicle Fuel Consumption Prediction Method Based on Driving Behavior Data Collected from Smartphones by Ying Yao, Xiaohua Zhao, Chang Liu, Jian Rong, Yunlong Zhang, Zhenning Dong, Yuelong Su

“…The results show that the average speed, average speed except for idle (ASEI), average acceleration, average deceleration, acceleration time percentage, deceleration time percentage, and cruising time percentage are important indicators for fuel consumption evaluation. All three models could predict fuel consumption accurately, with an absolute relative error less than 10%. …”
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An Improved Phase Space Reconstruction Method-Based Hybrid Model for Chaotic Traffic Flow Prediction by Yue Hou, Da Li, Di Zhang, Zhiyuan Deng

“…Meanwhile, the five error evaluation indexes of the proposed PDRGA-CDBN-LSTM hybrid model are lower than those of the baseline model, providing a new modeling idea for chaotic traffic flow prediction.…”
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Metro Shield Machine Attitude Prediction Method Integrating Excavation Index and Support Vector Regression by ZHANG Zhen, LIANG Jie, ZHANG Yulong, CHEN Tie, LIU Gang

“…The shield machine attitude prediction model is established using support vector regression method, which has advantages in small sample learning. …”
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SATF: a flight trajectory prediction method incorporating spatial awareness and time–frequency transformation by Jizhao Zhu, Zhuang Zhuang, Bing Han, Liang Zheng, Xinlong Pan

“…Extensive experiments are conducted on real-world Automatic Dependent Surveillance-Broadcast (ADS-B) datasets to evaluate the effectiveness of the proposed method. …”
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