tailieunhanh - An improved forecasting model combining recurrent fuzzy logical relationships and K-means clustering technique

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An improved forecasting model combining recurrent fuzzy logical relationships and K-means clustering technique

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In this paper, a new forecasting model based on combining the Fuzzy Time Series (FTS) and K-mean clustering algorithm with two concepts, the recurrent fuzzy relationship groups (RFRGs) and K-mean clustering technique, is presented. Firstly, the authors use the K-mean clustering algorithm to divide the historical data into clusters and adjust them into intervals with different lengths. | An improved forecasting model combining recurrent fuzzy logical relationships and K-means clustering technique

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An improved forecasting model combining recurrent fuzzy logical relationships and K-means clustering technique

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Đang chuẩn bị liên kết để tải về tài liệu: An improved forecasting model combining recurrent fuzzy logical relationships and K-means clustering technique

Extent of adoption level of improved maize production technology in Saharsa district of Bihar, India

Research and design of an improved solar still for desalination

Hybrid improved bacterial swarm optimization algorithm in hand based multimodal biometric authentication system

An improved action key frames extraction algorithm for complex colour video shot summarization

Constraints in adoption of improved cultivation practices of black gram

Adoption constraints of improved techniques for kitchen gardening in Chittorgarh district of Rajasthan, India

Stock price forecasting using support vector machines and improved particle swarm optimization

Comments on “A note on multi-objective improved teaching-learning based optimization algorithm (MO-ITLBO)”

A study on extent of adoption of improved cultivation practices by turmeric growers in Belagavi District, Karnataka, India

Impact assessment of improved technology on soybean productivity in south eastern Rajasthan, India

Đang chuẩn bị liên kết để tải về tài liệu:
An improved forecasting model combining recurrent fuzzy logical relationships and K-means clustering technique