Optimizing photovoltaic power plant forecasting with dynamic neural network structure refinement by Dácil Díaz-Bello, Carlos Vargas-Salgado, Manuel Alcazar-Ortega, David Alfonso-Solar

“…Despite advances in weather forecasting, photovoltaic power prediction accuracy remains a challenge. This study presents a novel approach that combines genetic algorithms and dynamic neural network structure refinement to optimize photovoltaic prediction. …”
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Interlayer Simplified Depth Coding for Quality Scalability on 3D High Efficiency Video Coding by Mengmeng Zhang, Hongyun Lu, Huihui Bai

“…A novel interlayer simplified depth coding (SDC) prediction tool is added to reduce the amount of bits for depth maps representation by exploiting the correlation between coding layers. …”
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A Novel Optimized Nonlinear Grey Bernoulli Model for Forecasting China’s GDP by Wen-Ze Wu, Tao Zhang, Chengli Zheng

“…The nonlinear grey Bernoulli model, abbreviated as NGBM(1,1), has been successfully applied to control, prediction, and decision-making fields, especially in the prediction of nonlinear small sample time series. …”
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Tourism Demand Forecasting Based on Grey Model and BP Neural Network by Xing Ma

“…This article aims to explore a more suitable prediction method for tourism complex environment, to improve the accuracy of tourism prediction results and to explore the development law of China’s domestic tourism so as to better serve the domestic tourism management and tourism decision-making. …”
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Research on Formation Identification Based on Drilling Shock and Vibration Parameters and Energy Principle by Yu Ding, Zhuoying Tan, Shuguang Li, Zizhen Miao, Huifen Qu

“…Based on the established drilling specific energy formula, the energy analysis method is used to predict the formation structure and compressive strength, and the corresponding prediction formula is given. …”
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Multivariate Load Forecasting of Integrated Energy System Based on CEEMDAN-CSO-LSTM-MTL by WANG Yongli, LIU Zeqiang, DONG Huanran, LI Dexin, CHEN Xin, GUO Lu, WANG Jiarui

“…The results show that compared with traditional prediction models，the constructed model can effectively improve the prediction accuracy of multiple loads in the integrated energy system.…”
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A Novel Power-Driven Grey Model with Whale Optimization Algorithm and Its Application in Forecasting the Residential Energy Consumption in China by Peng Zhang, Xin Ma, Kun She

“…Two validations on real-world datasets are conducted, and the results indicate that the power-driven grey model has significant advantages on the aspect of prediction performance compared with the other seven classical grey prediction methods. …”
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GABAergic neurons in the ventral tegmental area represent and regulate force vectors by Qiaochu Jiang, Konstantin I. Bakhurin, Ryan N. Hughes, Bryan Lu, Shaolin Ruan, Henry H. Yin

“…Previous work has suggested that VTA GABA neurons provide a reward prediction signal, which is used in computing a reward prediction error. …”
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Estimating the Concrete Compressive Strength Using Hard Clustering and Fuzzy Clustering Based Regression Techniques by Naresh Kumar Nagwani, Shirish V. Deo

“…Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. …”
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PV Power Forecasting in the Hexi Region of Gansu Province Based on AP Clustering and LSTNet by Xujiong Li, Guoming Yang, Jun Gou

“…The experimental comparison shows that the prediction model achieves high prediction accuracy and robustness.…”
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Application of big data technology in agricultural Internet of Things by Chunling Zhang, Zunfeng Liu

“…The Web Service technology is used to connect the Internet of Things with the neural network model to achieve data interoperability. By comparing the prediction results and actual data of the model, it is found that the prediction error of the model designed in this article is less than 1%, and the high-precision prediction of agricultural data is realized, which provides an effective guidance for the improvement of agricultural product quality and yield.…”
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Multiscale Deep Network with Centerness-Aware Loss for Salient Object Detection by Liangliang Duan

“…The proposed M2Net aims to solve saliency prediction and centerness prediction simultaneously. …”
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Design and Application of a Financial Distress Early Warning Model Based on Data Reasoning and Pattern Recognition by Xiaoya Hu

“…The empirical results show that the two models have good prediction effects. The prediction effect of the swarm optimization BP neural network model is better than that of the BP neural network model. …”
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Allelic Frequencies of 20 Visible Phenotype Variants in the Korean Population by Ji Eun Lim, Bermseok Oh

“…The prediction of externally visible characteristics from DNA has been studied for forensic genetics over the last few years. …”
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Data Imputation for Detected Traffic Volume of Freeway Using Regression of Multilayer Perceptron by Xiang Wang, Yingying Ma, Shengwen Huang, Yu Xu

“…The results of it show that the MAPE of prediction under the proposed model is much lower than all-zero imputation. …”
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Improving Regional Dynamic Downscaling with Multiple Linear Regression Model Using Components Principal Analysis: Precipitation over Amazon and Northeast Brazil by Aline Gomes da Silva, Claudio Moises Santos e Silva

“…Due to the atmosphere being a chaotic system, errors in predictions of future scenarios are systematically observed. …”
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Uncertainty Analysis of Multiple Hydrologic Models Using the Bayesian Model Averaging Method by Leihua Dong, Lihua Xiong, Kun-xia Yu

“…Since Bayesian Model Averaging (BMA) method can combine the forecasts of different models together to generate a new one which is expected to be better than any individual model’s forecast, it has been widely used in hydrology for ensemble hydrologic prediction. Previous studies of the BMA mostly focused on the comparison of the BMA mean prediction with each individual model’s prediction. …”
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Forecasting Natural Gas Consumption of China Using a Novel Grey Model by Chengli Zheng, Wen-Ze Wu, Jianming Jiang, Qi Li

“…As is known, natural gas consumption has been acted as an extremely important role in energy market of China, and this paper is to present a novel grey model which is based on the optimized nonhomogeneous grey model (ONGM (1,1)) in order to accurately predict natural gas consumption. This study begins with proving that prediction results are independent of the first entry of original series using the product theory of determinant; on this basis, it is a reliable approach by inserting an arbitrary number in front of the first entry of original series to extract messages, which has been proved that it is an appreciable approach to increase prediction accuracy of the traditional grey model in the earlier literature. …”
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Estimating Compressive Strength of High Performance Concrete with Gaussian Process Regression Model by Nhat-Duc Hoang, Anh-Duc Pham, Quoc-Lam Nguyen, Quang-Nhat Pham

“…Furthermore, GPR model is strongly recommended for estimating HPC strength because this method demonstrates good learning performance and can inherently express prediction outputs coupled with prediction intervals.…”
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Short-Term Forecasting of Dockless Bike-Sharing Demand with the Built Environment and Weather by Yang Yang, Xin Shao, Yuting Zhu, Enjian Yao, Dongmei Liu, Feng Zhao

“…To help related operators to allocate and dispatch the number of bike-sharing and provide good guidance for setting up electronic fences, this paper proposes a spatiotemporal graph convolution network prediction model (SGCNPM) with multiple factors to enhance the accuracy of predicting the demand for bike-sharing. …”
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