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Forecasting

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Systematic review of artificial intelligence-based image diagnosis for inflammatory bowel disease.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
OBJECTIVES: Diagnosis of inflammatory bowel diseases (IBD) involves combining clinical, laboratory, endoscopic, histologic, and radiographic data. Artificial intelligence (AI) is rapidly being developed in various fields of medicine, including IBD. B...

Dam deformation forecasting using SVM-DEGWO algorithm based on phase space reconstruction.

PloS one
A hybrid model integrating chaos theory, support vector machine (SVM) and the difference evolution grey wolf optimization (DEGWO) algorithm is developed to analyze and predict dam deformation. Firstly, the chaotic characteristics of the dam deformati...

Predicting Energy Consumption Using LSTM, Multi-Layer GRU and Drop-GRU Neural Networks.

Sensors (Basel, Switzerland)
With the steep rise in the development of smart grids and the current advancement in developing measuring infrastructure, short term power consumption forecasting has recently gained increasing attention. In fact, the prediction of future power loads...

Artificial Intelligence, Machine Learning and Smart Technologies for Nondestructive Evaluation.

Sensors (Basel, Switzerland)
Nondestructive evaluation (NDE) techniques are used in many industries to evaluate the properties of components and inspect for flaws and anomalies in structures without altering the part's integrity or causing damage to the component being tested. T...

Impact of digital transformation on the future of medical education and practice.

Journal of cardiac surgery
In this article, the author provides synopses of the factors that have finally propelled health-care education and practice to join, at times reluctantly, the overarching digital transformative process that has been swept other industries over the la...

Forecasting Carbon Price in China: A Multimodel Comparison.

International journal of environmental research and public health
With the global concern for carbon dioxide, the carbon emission trading market is becoming more and more important. An accurate forecast of carbon price plays a significant role in understanding the dynamics of the carbon trading market and achieving...

Forecasting large-scale circulation regimes using deformable convolutional neural networks and global spatiotemporal climate data.

Scientific reports
Classifying the state of the atmosphere into a finite number of large-scale circulation regimes is a popular way of investigating teleconnections, the predictability of severe weather events, and climate change. Here, we investigate a supervised mach...

An Optimization Analysis Model of Tourism Specialized Villages Based on Neural Network and System Dynamics.

Computational intelligence and neuroscience
With the rapid development of tourism, professional tourism villages emerge one after another, which has become the focus of the tourism industry. At present, there are some problems in tourism professional villages, such as imperfect management and ...

Algal bloom forecasting with time-frequency analysis: A hybrid deep learning approach.

Water research
The rapid emergence of deep learning long-short-term-memory (LSTM) technique presents a promising solution to algal bloom forecasting. However, the discontinuous and non-stationary processes within algal dynamics still largely limit the functions of ...

Deep Learning Applications in Surgery: Current Uses and Future Directions.

The American surgeon
Deep learning (DL) is a subset of machine learning that is rapidly gaining traction in surgical fields. Its tremendous capacity for powerful data-driven problem-solving has generated computational breakthroughs in many realms, with the fields of medi...