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Forecasting

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Temperature Prediction of Seasonal Frozen Subgrades Based on CEEMDAN-LSTM Hybrid Model.

Sensors (Basel, Switzerland)
Improving the temperature prediction accuracy for subgrades in seasonally frozen regions will greatly help improve the understanding of subgrades' thermal states. Due to the nonlinearity and non-stationarity of the temperature time series of subgrade...

Health Information Prediction System of Infant Sports Based on Deep Learning Network.

BioMed research international
The sensed data from infant sports and training programs are useful in analyzing their health conditions and forecasting any disorders or abnormalities. The sensed information is processed for providing errorless predictions for infant diseases/disor...

Research on Blended Teaching of Flipped Classroom Based on CNN-SSA-Bi-LSTM Deep Learning Model Computer Media.

Computational intelligence and neuroscience
Aiming at the problem that the influencing factors of computer media flipped classroom hybrid teaching lead to the teaching effect not reaching the expected, this study proposes an ultra-short-term prediction model based on CNN-SSA-Bi-LSTM. CNN-SSA-B...

Volatility forecasts of stock index futures in China and the US-A hybrid LSTM approach.

PloS one
This paper is concerned with the unsolved issue of how to accurately predict the financial market volatility. We propose a novel volatility prediction method for stock index futures prediction based on LSTM, PCA, stock indices and relevant futures. I...

Monocular Depth Estimation Using Deep Learning: A Review.

Sensors (Basel, Switzerland)
In current decades, significant advancements in robotics engineering and autonomous vehicles have improved the requirement for precise depth measurements. Depth estimation (DE) is a traditional task in computer vision that can be appropriately predic...

Short-Term Demand Forecast of E-Commerce Platform Based on ConvLSTM Network.

Computational intelligence and neuroscience
Based on real sales data, this article constructed LGBM and LSTM sales prediction models to compare and verify the performance of the proposed models. In this article, we forecast the product sales of stores in the future  + 3 days and use MAPE as th...

IGBT Fault Prediction Combining Terminal Characteristics and Artificial Intelligence Neural Network.

Computational and mathematical methods in medicine
The insulated gate bipolar transistor (IGBT) is widely utilized in the transportation, power, and energy domains because of its high input impedance and minimal on-voltage drop. IGBTs are frequently used in industrial applications for lengthy periods...

Prediction of Retail Price of Sporting Goods Based on LSTM Network.

Computational intelligence and neuroscience
Commodity prices play a unique role as a lever to regulate the economy. Price forecasting is an important part of macrodecision-making and micromanagement. Because there are many factors affecting the price of goods, price prediction has become a dif...

Construction of a Prediction Model for College Students' Psychological Disorders Based on Decision Systems and Improved Neural Networks.

Computational intelligence and neuroscience
Modeling and prediction of psychological disorders is a hot topic in current research. Neural networks are very important factors in improving the accuracy and precision ratios of the models which are developed for the prediction of the psychological...

Artificial Intelligence: Present and Future Potential for Solid Organ Transplantation.

Transplant international : official journal of the European Society for Organ Transplantation
Artificial intelligence (AI) refers to computer algorithms used to complete tasks that usually require human intelligence. Typical examples include complex decision-making and- image or speech analysis. AI application in healthcare is rapidly evolvin...