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Chapter and Conference Paper
Sliding Window GBDT for Electricity Demand Forecasting
Electricity consumption prediction plays a crucial role in energy management and urban planning. Accurate predictions enable utilities to optimize their power generation and distribution, while city planners c...
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Chapter and Conference Paper
Hybrid CNN-LSTM Model for Multi-industry Electricity Demand Prediction
Accurately predicting electricity demand is crucial for optimizing power resource allocation, improving the safety and economic performance of power grid operations, and providing significant economic and soci...
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Chapter and Conference Paper
Early Classification on Multivariate Time Series with Core Features
Multivariate time series (MTS) classification is an important topic in time series data mining, and has attracted great interest in recent years. However, early classification on MTS data largely remains a cha...
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Article
A multi-agent reinforcement learning approach to robot soccer
In this paper, a multi-agent reinforcement learning method based on action prediction of other agent is proposed. In a multi-agent system, action selection of the learning agent is unavoidably impacted by othe...
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Chapter and Conference Paper
Robot Navigation Based on Fuzzy RL Algorithm
This paper focused on the problem of the autonomous mobile robot navigation under the unknown and changing environment. The reinforcement learning (RL) is applied to learn behaviors of reactive robot. T-S fuzz...
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Chapter and Conference Paper
State Space Partition for Reinforcement Learning Based on Fuzzy Min-Max Neural Network
In this paper, a tabular reinforcement learning (RL) method is proposed based on improved fuzzy min-max (FMM) neural network. The method is named FMM-RL. The FMM neural network is used to segment the state spa...