Search results

This study aims to improve the offshore wind farm (OWF) site selection evaluation index system and establishes a decision-making model for OWF site selection. It is expected to provide helpful references for the progress of offshore wind power.

Firstly, this paper establishes an evaluation criteria system for OWF site selection, considering six criteria (wind resource, environment, economic, technical, social and risk) and related subcriteria. Then, the Criteria Importance Though Intercrieria Correlation (CRITIC) method is introduced to figure out the weights of evaluation indexes. In addition, the cumulative prospect theory and technique for order preference by similarity to an ideal solution (CPT-TOPSIS) method are employed to construct the OWF site selection decision-making model. Finally, taking the OWF site selection in China as an example, the effectiveness and robustness of the framework are verified by sensitivity analysis and comparative analysis.

This study establishes the OWF site selection evaluation system and constructs a decision-making model under the spherical fuzzy environment. A case of China is employed to verify the effectiveness and feasibility of the model.

In this paper, a new decision-making model is proposed for the first time, considering the ambiguity and uncertainty of information and the risk attitudes of decision-makers (DMs) in the decision-making process.

In the process of vigorously promoting urbanization, the city development became a new driving force for China's prosperity. To comprehensively analyze the urban regional innovation system, the typical urban city was taken as an empirical sample to consider as an urban regional innovation system. The fuzzy comprehensive evaluation method was used to evaluate the operation of typical urban regional innovation system, combined the cluster analysis and Bayesian discrimination for the research and analysis. The results showed that the evaluation of regional innovation system was a national innovation strategy. Therefore, the model provides an important evidence for the urban innovative development. The proposed targeted innovation development strategy is conducive to grasp the advantages and disadvantages of the typical urban regional innovation system construction as a whole. The analysis of the structural change layers and sub-distribution of urban regional innovation effectiveness helps to clarify the stage of urban development.

The COVID-19 pandemic has dramatically disrupted everyday life, leading to a cascade of negative emotional responses such as death anxiety. Against this backdrop, the purpose of this paper is to focus on the buffering effect of brand attachment on death anxiety by exploring the roles of brand concepts and brand positioning on psychological compensation for security.

This multi-method paper features four studies and shows how brands can offer emotional support under high-risk circumstances.

Study 1 includes two surveys which offer preliminary evidence that death anxiety can enhance consumers’ brand attachment. Study 2 reveals a causal effect wherein consumers experiencing death anxiety are more likely to attach to brands with a self-transcendence (vs self-enhancement) concept. Study 3 examines the mediating role of need for security in the relationship between death anxiety and attachment to brands with a self-transcendence concept. Further, Study 4 indicates the moderating role of brand positioning: self-transcendence brands adopting local (vs global) positioning strategies are more likely to satisfy consumers’ need for security, thereby leading to strong brand attachment.

The findings of this paper contribute to the brand attachment literature and to the global branding literature regarding consumers’ emotional responses in the context of COVID-19. This paper innovatively frames brand concepts and brand positioning and provides actionable guidelines to help brands satisfy consumers’ needs amid a worldwide crisis.

The purpose of this paper is to use the wavelet neural network and genetic algorithm to study the effects of polyalphaolefin, TMP108 and OCP0016 on the kinematic viscosity, viscosity index and pour point of lubricating oil.

Wavelet neural network is used to train the known samples, test the unknown samples and compare the obtained results with those obtained with a traditional empirical formula.

It is found that the wavelet neural network prediction value is closer to the experimental value than the traditional empirical formula calculation value.

The results show that the wavelet neural network can be used to study the physical and chemical indexes of lubricating oil.

This paper aims to solve the problems of the synchronization between branches and the uncertainties such as joint friction, load variation and external interference of a hybrid mechanism. The controller is used to improve the synchronization and robustness of the hybrid mechanism system and achieve both finite time convergence and chattering-free sliding mode.

First, the dynamic model of hybrid mechanism containing lumped uncertainties is formulated by the Lagrange method, and a composite error based on coupling synchronization error and the end-effector tracking error is set up in the task space. Then, by combining the finite time super twisting sliding mode control algorithm, a composite error-based finite time super twisting sliding mode synchronous control law is designed to make the end-effector tracking error and coupling synchronization error achieve better tracking performance and convergence performance. Finally, the Lyapunov stability of the control law and the finite-time convergence of the composite error are proved theoretically.

To verify the effectiveness of the proposed control method, simulations and experiments for the prototype system of the hybrid mechanism are conducted. The results show that the proposed control method can achieve better tracking performance and convergence performance.

This is a new innovation for a hybrid mechanism containing lumped uncertainties to improve the robustness, convergence performance, tracking performance and synchronization of the system.

Korea and China have promoted a bilateral FTA since 2005 to upgrade their economic relationships. If the Korea-China FTA is concluded, then trade between the two countries is likely to involve substantial changes both quantitatively and qualitatively. Offer lists submitted by Korea include steel, petrochemicals and machinery and those by China include some agricultural and marine products as well as nonferrous metals. Korea's interest in the Korea-China FTA has focused mainly on damage to the agricultural sector and there have been a lot of studies on the effects of the FTA on Korean agricultural sector. However, little is known about why China includes the nonferrous metals industry for early voluntary liberalization and its implications for the domestic economy. Nonferrous metals industry is one of China’s national strategic sectors and has a large supply excess in the country. This study targets the survey of Chinese nonferrous metals industry and trade structure and considers the problem of nonferrous metals in the context of negotiations for the Korea-China FTA and its implications for a higher-quality Korea-China FTA.

Bankruptcy is a financial failure of a business or an organization. Different kinds of bankruptcy prediction techniques are proposed to predict it. But, they are restricted as techniques in predicting the bankruptcy and not addressing the associated activities like acquiring the suitable data and delivering the results to the user after processing it. This situation demands to look for a comprehensive solution for predicting bankruptcy with intelligence. The paper aims to discuss these issues.

To model Business Intelligence (BI) solution for BP the concept of reference model is used. A Reference Model for Business Intelligence to Predict Bankruptcy (RMBIPB) is designed by applying unit operations as hierarchical structure with abstract components. The layers of RMBIPB are constructed from the hierarchical structure of the model and the components, which are part of the reference model. In this model, each layer is designed based on the functional requirements of the Business Intelligence System (BIS).

This reference model exhibits the non functional software qualities intended for the appropriate unit operations. It has flexible design in which techniques are selected with minimal effort to conduct the bankruptcy prediction. The same reference model for another domain can be implemented with different kinds of techniques for bankruptcy prediction.

This model is designed using unit operations and the software qualities exhibited by RMBIPB are limited by unit operations. The data set which is applied in RMBIPB is limited to Indian banks.

A comprehensive bankruptcy prediction model using BI with customized reporting.