Two improved k-means algorithms
K-means algorithm is the most commonly used simple clustering method. For a large
number of high dimensional numerical data, it provides an efficient method for classifying …
number of high dimensional numerical data, it provides an efficient method for classifying …
Customer decision-making analysis based on big social data using machine learning: a case study of hotels in Mecca
A Alsayat - Neural Computing and Applications, 2023 - Springer
Big social data and user-generated content have emerged as important sources of timely
and rich knowledge to detect customers' behavioral patterns. Revealing customer …
and rich knowledge to detect customers' behavioral patterns. Revealing customer …
Regionalization of water environmental carrying capacity for supporting the sustainable water resources management and development in China
Z Jia, Y Cai, Y Chen, W Zeng - Resources, Conservation and Recycling, 2018 - Elsevier
With the rapid economic growth and social development in China, conflicts over water
resources between human and nature are continuously increasing which is attracting the …
resources between human and nature are continuously increasing which is attracting the …
A hybrid wind power forecasting model based on data mining and wavelets analysis
Accurate forecasting of wind power plays a key role in energy balancing and wind power
integration into the grid. This paper proposes a novel time-series based K-means clustering …
integration into the grid. This paper proposes a novel time-series based K-means clustering …
A hybrid method based on a new clustering technique and multilayer perceptron neural networks for hourly solar radiation forecasting
Accurate forecasting of renewable energy sources plays a key role in their integration into
the grid. This paper proposes a hybrid solar irradiance forecasting framework using a …
the grid. This paper proposes a hybrid solar irradiance forecasting framework using a …
The spatiotemporal response of China's vegetation greenness to human socio-economic activities
Climate change and human socioeconomic activities both strongly impact long-term
vegetation greenness. It is more a challenge to evaluate the impacts of socioeconomic …
vegetation greenness. It is more a challenge to evaluate the impacts of socioeconomic …
Emulation of high-performance correlation-based quantum clustering algorithm for two-dimensional data on FPGA
Clustering algorithms are used to classify the unlabeled data into a number of categories
with polynomial time complexity. Quantum clustering algorithms are developed to improve …
with polynomial time complexity. Quantum clustering algorithms are developed to improve …
Optimum-path forest based on k-connectivity: Theory and applications
Graph-based pattern recognition techniques have been in the spotlight for many years,
since there is a constant need for faster and more effective approaches. Among them, the …
since there is a constant need for faster and more effective approaches. Among them, the …
A novel soft computing framework for solar radiation forecasting
Accurate forecasting of renewable-energy sources plays a key role in their integration into
the grid. This paper proposes a novel soft computing framework using a modified clustering …
the grid. This paper proposes a novel soft computing framework using a modified clustering …
Spatiotemporal characteristics of China's carbon emissions and driving forces: A Five-Year Plan perspective from 2001 to 2015
C Gao, H Ge - Journal of Cleaner Production, 2020 - Elsevier
Abstract China's Five-Year Strategic Plan for National Economic and Social Development
(FYP) sets up development goals, main tasks, and policy measures to regulate or facilitate …
(FYP) sets up development goals, main tasks, and policy measures to regulate or facilitate …