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Adaptive data processing framework for efficient short-term traffic flow prediction
Accurate short-term traffic forecasting is a prerequisite for establishing intelligent transportation systems. In this paper, a new adaptive traffic...
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Short-Term Traffic Flow Forecast Based on ARIMA-SVM Combined Model
Short-term traffic flow prediction is an important basis for traffic state discrimination and traffic congestion prediction. The ARIMA-SVM combined...
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Emotion Recognition Using Ultra-Short-Term ECG Signals with a Hybrid Convolutional Neural Network and Long Short-Term Memory Network
This research aims to investigate emotion recognition using ultra-short-term electrocardiogram (ECG) signals with a hybrid convolutional neural...
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Short - Term Power Load Forecasting Algorithm Based on Combination Forecasting Method
Power load prediction is very important for power supply stability and power supply pressure control, and short-term power load prediction is the...
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A Hybrid Framework Combining LSTM NN and BNN for Short-term Traffic Flow Prediction and Uncertainty Quantification
Short-term traffic flow prediction plays a critical role in Intelligent Transportation System (ITS), and has attracted continuous attention. Previous...
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Residential Level Short-Term Demand Forecasting Using ANFIS Model
Forecasting is a process in which future demand is predicted with the help of past and current data. Uncertainty in real-world data makes this...
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Short-term load forecasting method based on fuzzy optimization combined model of load feature recognition
With the continuous development of smart grid construction and the gradual improvement of power market operation mechanisms, the importance of power...
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Air Pollution Prediction Using Long Short-Term Memory Variants
Air pollution is an unresolved environmental problem that poses a health threat in many countries. Nearly 90% of the global population is exposed to...
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A noise-immune and attention-based multi-modal framework for short-term traffic flow forecasting
Accurately forecasting short-term traffic flow is essential for intelligent transportation systems. However, current methods often struggle to fully...
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Short-term Power Load Forecasting Based on Phase Space Reconstruction and EMD-ELM
With the increasing complexity of the world energy structure, the uncertainty of the power system increases significantly, and the accuracy of the...
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Investigation of Artificial Intelligence Methods in the Short-Term and Middle-Term Forecasting in Financial Sphere
In this paper the problems of short- and middle-term forecasting at the financial sphere are considered. For this problem intelligent forecasting...
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Helicopter short-term collision avoidance with sampling-based model predictive control
Automatic helicopter flight in uncertain surroundings remains a challenging task due to sudden changes in environment, requiring fast response to...
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Adaptive hyperparameter optimization for short term traffic flow prediction with spatial temporal correlated raster data
IoT-based Intelligent transport system(ITS) is an innovative solution to urban traffic problems by providing different modes of traffic, traffic...
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Short-Term Load Forecasting Using Machine Learning Algorithms
In meeting the ever-increasing demand for power, electric power distributors must be well-equipped with a prediction mechanism that can accurately...
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Knowledge-Data Fusion Model for Multivariate Load Short-Term Forecasting of Integrated Energy System
The short-term forecasting of multiple loads is crucial for the optimization and scheduling of integrated energy system (IES). However, the load...
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Short-term Wind Power Prediction Based on LSTM Considering Power Fluctuation Characteristics
Good wind power predictions of wind farms can provide data support for system planning and operation scheduling. In this paper, a short-term wind...
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Short-Term Schedule Optimization with Nonlinear Blending Models for Improved Metallurgical Recovery in Mining
In mining and mineral processing operations, ore blending is an inherent practice, as individual ore blocks are seldom processed in isolation but...
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Linear-layer-enhanced quantum long short-term memory for carbon price forecasting
Accurate carbon price forecasting is important for investors and policymakers to make decisions in the carbon market. With the development of quantum...
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Evolution of modal parameters of composite wind turbine blades under short- and long-term forced vibration tests
Modal properties of dynamically tested wind turbine blades (WTBs) of a utility-scale wind turbine are identified. A comprehensive experimental...
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Short-term rockburst prediction in underground project: insights from an explainable and interpretable ensemble learning model
Rockburst is a frequent challenge during tunnel and other underground construction and is an extreme rock damage phenomenon. Therefore, it is very...
