Chung-Han Ho, Ping-Teng Chang, Kuo-Chen Hung and Kuo-Ping Lin
The purpose of this paper is to develop a novel intuitionistic fuzzy seasonality regression (IFSR) with particle swarm optimization (PSO) algorithms to accurately forecast air…
Abstract
Purpose
The purpose of this paper is to develop a novel intuitionistic fuzzy seasonality regression (IFSR) with particle swarm optimization (PSO) algorithms to accurately forecast air pollutions, which are typical seasonal time series data. Seasonal time series prediction is a critical topic, and some time series data contain uncertain or unpredictable factors. To handle such seasonal factors and uncertain forecasting seasonal time series data, the proposed IFSR with the PSO method effectively extends the intuitionistic fuzzy linear regression (IFLR).
Design/methodology/approach
The prediction model sets up IFLR with spreads unrestricted so as to correctly approach the trend of seasonal time series data when the decomposition method is used. PSO algorithms were simultaneously employed to select the parameters of the IFSR model. In this study, IFSR with the PSO method was first compared with fuzzy seasonality regression, providing evidence that the concept of the intuitionistic fuzzy set can improve performance in forecasting the daily concentration of carbon monoxide (CO). Furthermore, the risk management system also implemented is based on the forecasting results for decision-maker.
Findings
Seasonal autoregressive integrated moving average and deep belief network were then employed as comparative models for forecasting the daily concentration of CO. The empirical results of the proposed IFSR with PSO model revealed improved performance regarding forecasting accuracy, compared with the other methods.
Originality/value
This study presents IFSR with PSO to accurately forecast air pollutions. The proposed IFSR with PSO model can efficiently provide credible values of prediction for seasonal time series data in uncertain environments.
Details
Keywords
Yating Zhang, Chung-Han Tsai, Wei Liu and Kun Weng
This research examines farmers’ cognitions to the policy and how such cognitions influence their intentions and behaviors of land transfer, with the implementation of the Three…
Abstract
Purpose
This research examines farmers’ cognitions to the policy and how such cognitions influence their intentions and behaviors of land transfer, with the implementation of the Three Rights Separation (TRS) policy.
Design/methodology/approach
Using data collected from the Beijing area, this research tests the relationship between farmers’ policy cognition and their intention/behavior through the mediation of their psychological constructs. Both Causal step test and Bootstrap test are adopted.
Findings
Farmers’ intention of land transfer is influenced by their cognition of the TRS policy. In this process, farmers’ psychological constructs play a mediating role between their policy cognition and their intentions of land transfer, thereby eventually influencing their behaviors. This research confirms that institutions are not exogenous and the policy is not wishful thinking from the government. Instead, any policies, even enacted by governmental authority, have to be internalized within target groups’ cognition to be implemented.
Originality/value
Land transfer deserves close attention since it is the direct aim of the TRS reform. In this regard, this paper, based on an institutional perspective, aims to extend our understanding on the incentives of land transfer. This research proposes a revised model of planned behavior and argues that farmers’ intention of land transfer is influenced by their cognition of the TRS policy. On one hand, this study is the first to examine farmers’ cognition formed through the implementation of the TRS policy. On the other hand, it reveals the path of how policy can finally influence farmers’ intentions and behaviors through shaping their cognitions and changing subjective perceptions, which enriches our understanding of the mechanism of how policy has a concrete impact on society.
Details
Keywords
Rapid development of IT and communication technologies resulted in the “Smart” concept, which of late has become quite popular. The smart concept signifies the integration of…
Abstract
Rapid development of IT and communication technologies resulted in the “Smart” concept, which of late has become quite popular. The smart concept signifies the integration of organizational networks and smart features that enrich the ecosystem, facilitate daily activities for all stakeholders, and for automatization. Smart concept was discussed as a complicated technological infrastructure in urban areas intended to promote economic, social and environmental welfare. The latest technological developments gave rise to the concepts of smart planet, smart city and smart destination that have become important in recent years. Technological innovations have had a big influence on the development of the tourism industry. Smart concept is conceptualized as smart tourism for tourism sector. Smart Tourism generally has a positive effect on the rapid change of information and technology and on the tourism sector, tourism activities and increase in customer satisfaction. In this chapter, the concept of Smart and its smart technologies are explained and information about its reflections on the tourism sector and smart tourism destinations are discussed.
Details
Keywords
Rahime Zaman Fashami, Manijeh Haghighinasab, Nader Seyyedamiri and Pari Ahadi