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Article
Publication date: 16 August 2022

Zibo Li, Zhengxiang Yan, Shicheng Li, Guangmin Sun, Xin Wang, Dequn Zhao, Yu Li and Xiucheng Liu

The purpose of this paper is to overcome the application limitations of other multi-variable regression based on polynomials due to the huge computation room and time cost.

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Abstract

Purpose

The purpose of this paper is to overcome the application limitations of other multi-variable regression based on polynomials due to the huge computation room and time cost.

Design/methodology/approach

In this paper, based on the idea of feature selection and cascaded regression, two strategies including Laguerre polynomials and manifolds optimization are proposed to enhance the accuracy of multi-variable regression. Laguerre polynomials were combined with the genetic algorithm to enhance the capacity of polynomials approximation and the manifolds optimization method was introduced to solve the co-related optimization problem.

Findings

Two multi-variable Laguerre polynomials regression methods are designed. Firstly, Laguerre polynomials are combined with feature selection method. Secondly, manifolds component analysis is adopted in cascaded Laguerre polynomials regression method. Two methods are brought to enhance the accuracy of multi-variable regression method.

Research limitations/implications

With the increasing number of variables in regression problem, the stable accuracy performance might not be kept by using manifold-based optimization method. Moreover, the methods mentioned in this paper are not suitable for the classification problem.

Originality/value

Experiments are conducted on three types of datasets to evaluate the performance of the proposed regression methods. The best accuracy was achieved by the combination of cascade, manifold optimization and Chebyshev polynomials, which implies that the manifolds optimization has stronger contribution than the genetic algorithm and Laguerre polynomials.

Details

Engineering Computations, vol. 39 no. 8
Type: Research Article
ISSN: 0264-4401

Keywords

Available. Content available
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Publication date: 15 November 2018

Yi-Ming Wei and Hua Liao

Abstract

Details

Energy Economics
Type: Book
ISBN: 978-1-78756-780-1

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Article
Publication date: 7 October 2014

Martin Aruldoss, Miranda Lakshmi Travis and V. Prasanna Venkatesan

Business intelligence (BI) has been applied in various domains to take better decisions and it provides different level of information to its stakeholders according to the…

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Abstract

Purpose

Business intelligence (BI) has been applied in various domains to take better decisions and it provides different level of information to its stakeholders according to the information needs. The purpose of this paper is to present a literature review on recent works in BI. The two principal aims in this survey are to identify areas lacking in recent research, thereby offering potential opportunities for investigation.

Design/methodology/approach

To simplify the study on BI literature, it is segregated into seven categories according to the usage. Each category of work is analyzed using parameters such as purpose, domain, problem identified, solution applied, benefit and outcome.

Findings

The BI contribution in various domains, ongoing research in BI, the convergence of BI domains, problems and solutions, results of congregated domains, core problems and key solutions. It also outlines BI and its components composition, widely applied BI solutions such as algorithm-based, architecture-based and model-based solutions. Finally, it discusses BI implementation issues and outlines the security and privacy policies adopted in BI environment.

Research limitations/implications

In this survey BI has been discussed in theoretical perspective whereas practical contribution has been given less attention.

Originality/value

A comprehensive survey on BI which identifies areas lacking in recent research and providing potential opportunities for investigation.

Details

Journal of Enterprise Information Management, vol. 27 no. 6
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 15 December 2021

Yin Shi, Liping Ding, Chenchen He, Fan Zhang, Zumeng Zhang and Qiyao Dai

This study aims to analyze those factors affecting the rural resident’s willingness to adopt solar photovoltaic (PV) which is important for accelerating the popularization of…

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Abstract

Purpose

This study aims to analyze those factors affecting the rural resident’s willingness to adopt solar photovoltaic (PV) which is important for accelerating the popularization of clean energy in China.

Design/methodology/approach

This study contained a sample of 653 households in 8 provinces/regions by stratified, and random sampling in rural China. Descriptive analysis, exploratory factor analysis and confirmatory factor analysis techniques have been used for analytical purposes.

Findings

The empirical results indicate that financial incentive and social interaction have positive effects on rural residents’ adoption willingness, while village leaders’ engagement can indirectly influence their adoption willingness through social interaction and residents’ cognition.

Research limitations/implications

This study mainly considers external and internal factors but ignores the effect of technical factors. In addition, the samples are just selected from the residents who have adopted solar PV.

Practical implications

This study is expected to be useful for the government, regulators, village leaders, village leaders and other institutions.

Originality/value

This study conducts a systematic analysis and clarifies the relationship between factors (external and internal) and rural residents’ adoption willingness. The village leaders’ engagement is first added to the conceptual model as an external factor, which is very essential in rural residents’ adoption in China.

Details

International Journal of Energy Sector Management, vol. 16 no. 5
Type: Research Article
ISSN: 1750-6220

Keywords

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