AIMC Topic: Forecasting

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Analysis of environmental factors using AI and ML methods.

Scientific reports
The main goal of this research paper is to apply a deep neural network model for time series forecasting of environmental variables. Accurate forecasting of snow cover and NDVI are important issues for the reliable and efficient hydrological models a...

The Prediction of Enterprise Stock Change Trend by Deep Neural Network Model.

Computational intelligence and neuroscience
This study aims to accurately predict the changing trend of stocks in stock trading so that company investors can obtain higher returns. In building a financial forecasting model, historical data and learned parameters are used to predict future stoc...

Automatic grading for Arabic short answer questions using optimized deep learning model.

PloS one
Auto-grading of short answer questions is considered a challenging problem in the processing of natural language. It requires a system to comprehend the free text answers to automatically assign a grade for a student answer compared to one or more mo...

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...