Application of the BP Neural Network Model of Gray Relational Analysis in Economic Management by Zhuojie Li

“…The results show that the new model can comprehensively and extensively process a large number of input variables by using the concept of the gray correlation degree, without having to go through special subjective screening and hence improving the adaptability of the BP network, and at the same time, it can obtain better prediction accuracy and stability. Through the empirical test, the prediction ability of the three methods of regression, GM (1, N) gray system, and GM-BPANN model is compared. …”
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Crack Identification Method of Steel Fiber Reinforced Concrete Based on Deep Learning: A Comparative Study and Shared Crack Database by Yang Ding, Shuang-Xi Zhou, Hai-Qiang Yuan, Yuan Pan, Jing-Liang Dong, Zhong-Ping Wang, Tong-Lin Yang, An-Ming She

“…In addition, the improved Mask R-CNN method is proposed in order to improve the prediction accuracy based on the Mask R-CNN. The results show that the average prediction accuracy of concrete crack identification is 82.60% based on the YOLO v4 method. …”
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Machine Learning Classification Techniques for Detecting the Impact of Human Resources Outcomes on Commercial Banks Performance by Sulaiman O. Atiku, Ibidun C. Obagbuwa

“…Most researchers in the past adopted traditional statistics to build prediction models; however, due to the efficiency of machine learning algorithms, a lot of researchers now apply various machine learning algorithms to various fields, including performance prediction systems. …”
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Soil-Landscape Modeling and Remote Sensing to Provide Spatial Representation of Soil Attributes for an Ethiopian Watershed by Nurhussen Mehammednur Seid, Birru Yitaferu, Kibebew Kibret, Feras Ziadat

“…The use of satellite images improved the prediction. The soil depth prediction accuracy dropped gradually from 98% when 180 field observations were used to 65% using only 25 field observations. …”
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A Hybrid Approach Integrating Multiple ICEEMDANs, WOA, and RVFL Networks for Economic and Financial Time Series Forecasting by Jiang Wu, Tengfei Zhou, Taiyong Li

“…Then, we aggregate the prediction results of individual decomposed subseries as the prediction results of each decomposition, respectively, and finally integrate these prediction results of all the decompositions as the final ensemble prediction results. …”
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Multifractal Analysis of Acoustic Emissions during Hydraulic Fracturing Experiments under Uniaxial Loading Conditions: A Niutitang Shale Example by Jingqiang Tan, Jun Xie, Lei Li, Qiao Lyu, Jianqiang Han, Zhengguang Zhao

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Petrophysical Regression regarding Porosity, Permeability, and Water Saturation Driven by Logging-Based Ensemble and Transfer Learnings: A Case Study of Sandy-Mud Reservoirs by Shenghan Zhang, Yufeng Gu, Yinshan Gao, Xinxing Wang, Daoyong Zhang, Liming Zhou

“…Light gradient boosting machine (LightGBM) is proved as one representative of the state-of-the-art ensemble learning, thus adopted as a potential solver to predict three target reservoir characters. To guarantee the predicting quality of LightGBM, continuous restricted Boltzmann machine (CRBM) and Bayesian optimization (Bayes) are introduced as assistants to enhance the significance of input logs and the setting of employed hyperparameters. …”
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Enhancing Drought Forecast Accuracy Through Informer Model Optimization by Jieru Wei, Wensheng Tang, Pakorn Ditthakit, Jiandong Shang, Hengliang Guo, Bei Zhao, Gang Wu, Yang Guo

“…As droughts become more frequent due to climate change and shifts in land use, enhancing the accuracy of drought prediction is becoming crucial for informed land and water resource management. …”
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Enhanced Influence of Late‐Winter Arctic Oscillation on Early Spring Temperature in North and Northeast Asia by Xin Zhou, Tingting Han, Huijun Wang, Botao Zhou, Shengping He

“…However, the stability of the precursor signals in AO for Asian surface air temperature (SAT), which is important for short‐term climate prediction, has received little attention. In this study, a strengthened relationship is identified between the late‐winter AO and the early spring SAT over North and Northeast Asia (NNA) around the 1990s. …”
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Early warning systems (EWSs) for chikungunya, dengue, malaria, yellow fever, and Zika outbreaks: What is the evidence? A scoping review. by Laith Hussain-Alkhateeb, Tatiana Rivera Ramírez, Axel Kroeger, Ernesto Gozzer, Silvia Runge-Ranzinger

“…Key findings were the following: (1) a large number of studies showed the quality performance of their prediction models but except for dengue outbreaks, only few presented statistical prediction validity of EWS; (2) while entomological, epidemiological, and social media alarm indicators are potentially useful for outbreak warning, almost all studies focus primarily or exclusively on meteorological indicators, which tends to limit the prediction capacity; (3) no assessment of the integration of the EWS into a routine surveillance system could be found, and only few studies addressed the users' perspective of the tool; (4) almost all EWS tools require highly skilled users with advanced statistics; and (5) spatial prediction remains a limitation with no tool currently able to map high transmission areas at small spatial level.…”
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Coupling natural-social models can better quantify the interactions in achieving carbon neutrality in China by Tianpeng Wang, Yixiong Lu, Fei Teng, Xiliang Zhang, Xiaoye Zhang, Min Wei, Tongwen Wu, Deying Wang, Jing Sun, Junting Zhong

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Estimation of car braking parameters by Marijus Radavičius, Saulius Nagurnas

“… In the paper the problem of prediction of car braking distance from its initial speed is considered. …”
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A Fuzzy Soft Model for Haze Pollution Management in Northern Thailand by Parkpoom Phetpradap

“…The results show that our fuzzy models improve the prediction accuracy ratio compared to the prediction based on PM10 density only. …”
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Exploiting the similarity of dissimilarities for biomedical applications and enhanced machine learning. by Mohammad Neamul Kabir, Li Rong Wang, Wilson Wen Bin Goh

“…The "similarity of dissimilarities" is an emerging paradigm in biomedical science with significant implications for protein function prediction, machine learning (ML), and personalized medicine. …”
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Multisensor Data and Cross-Validation Technique for Merging Temporal Images for the Agricultural Performance Monitoring System by Venkata Kanaka Srivani Maddala, K. Jayarajan, M. Braveen, Ranjan Walia, Patteti Krishna, Sivakumar Ponnusamy, Karthikeyan Kaliyaperumal

“…The proposed technique’s excellent reliability on crop yield prediction is compared and contrasted between crop yield prediction and actual production in different areas, and meaningful observations are provided.…”
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Historical Feature Pattern Extraction Based Network Attack Situation Sensing Algorithm by Yong Zeng, Dacheng Liu, Zhou Lei

“…Then it calculates the probability that a certain effect reappears according to the current indication and makes a prediction after weighting. Meanwhile, HFPE method gives an evolution algorithm to derive the prediction deviation from the views of pattern and accuracy. …”
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Prognostic Factors for COVID-19 Hospitalized Patients with Preexisting Type 2 Diabetes by Yuanyuan Fu, Ling Hu, Hong-Wei Ren, Yi Zuo, Shaoqiu Chen, Qiu-Shi Zhang, Chen Shao, Yao Ma, Lin Wu, Jun-Jie Hao, Chuan-Zhen Wang, Zhanwei Wang, Richard Yanagihara, Youping Deng

“…An individualized risk prediction nomogram was developed and evaluated by discrimination and calibration. …”
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Study on the Calibration Transfer of Soil Nutrient Concentration from the Hyperspectral Camera to the Normal Spectrometer by Xue-Ying Li, Guo-xing Ren, Ping-Ping Fan, Yan Liu, Zhong-Liang Sun, Guang-Li Hou, Mei-Rong Lv

“…The absolute coefficients Rt2 and root mean square error of prediction (RMSEP) were used to evaluate the prediction performance after calibration transfer. …”
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Seasonal variation of underwater sound propagation in the Beibu Gulf by Feihong Zeng, Feihong Zeng, Lingling Xie, Lingling Xie, Lingling Xie, Mingming Li, Mingming Li, Mingming Li, Qiang Li, Qiang Li, Qiang Li, Simeng Liu, Simeng Liu

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Multi-source meteorological data assessment on daily runoff simulation in the upper reaches of the Hei River, Northwest China by Huazhu Xue, Yaheng Wang, Guotao Dong, Chenchen Zhang, Yaokang Lian, Hui Wu

“…Considering the impact of meteorological data on runoff simulation and prediction, meteorological station observation data, ERA5 data and CFSv2 data were obtained for runoff simulation and prediction. …”
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