In this paper, a network traffic forecasting model based on long-term intuitionistic fuzzy time series (LT-IFTS) is proposed. It describes the fuzziness and uncertainty of network flow and improves the traffic forecasting performance. The multi-input multi-output (MIMO) intuitionistic fuzzy time series forecasting model, namely, ( − ) IFTS is defined. An intuitionistic fuzzy time series vectors clustering algorithm based on vector variation pattern is given. The cluster centroid in the proposed model is quite different from the traditional method. As a kind of typical time series data, the network flow forecasting system is constructed particularly. Characteristic intuitionistic fuzzy is a practical method to manage the fuzziness and uncertainty of network traffic data. The network traffic data is intuitionistic fuzzified and vector quantized. The time series vectors are gathered based on the improved intuitionistic fuzzy -means clustering and matched with centroids by coordinate translation. Compared with other traditional forecasting models, the improved FCM clustering algorithm increases discrimination of time series segments. In addition, the long-term scheme improves forecasting efficiency and reduces computational complexity than other single-output models. In experiments, the proposed model and relevant models are implemented on four different scales network traffic dataset from MAWI. The experiment result indicates that the proposed model is with better generalization performance.
Stability evaluation of a slope involves various fuzzy and correlation indicators randomly distributed in finite intervals. A novel multi-dimensional connection cloud model was presented here to address multiple uncertainties and distribution characteristics of indicators, and to depict the randomness and fuzziness of the measured index value belonging to the classification standard in the slope stability analysis. In the model, when simulating fuzzy and random characteristics of evaluation indicators in finite intervals, the numerical characteristics of connection cloud model were assigned on the basis of the analysis of identical-discrepancy-contrary (IDC) relationships between measured indicators and the classification standard to overcome the subjectivity. Considering the effect of indicator correlation in a unified way, the integrated connection degree of a grade was further specified for the evaluation sample. Moreover, case studies and comparisons of the proposed model with one-dimensional normal cloud model, extension model, and support vector machine (SVM) were performed to confirm the validity and reliability. The results indicate that this model employed to evaluate slope stability can clearly depict the random and fuzzy distribution features of measured data in finite intervals, and its calculation process is quicker and simpler than that of one-dimensional normal cloud model.
Supplier selection problem has gained extensive attention in the prior studies. However, research based on Fuzzy Multi-Attribute Decision Making (F-MADM) approach in ranking resilient suppliers in logistic 4.0 is still in its infancy. Traditional MADM approach fails to address the resilient supplier selection problem in logistic 4.0 primarily because of the large amount of data concerning some attributes that are quantitative, yet difficult to process while making decisions. Besides, some qualitative attributes prevalent in logistic 4.0 entail imprecise perceptual or judgmental decision relevant information, and are substantially different than those considered in traditional suppler selection problems. This study develops a Decision Support System (DSS) that will help the decision maker to incorporate and process such imprecise heterogeneous data in a unified framework to rank a set of resilient suppliers in the logistic 4.0 environment. The proposed framework induces a triangular fuzzy number from large-scale temporal data using probability-possibility consistency principle. Large number of non-temporal data presented graphically are computed by extracting granular information that are imprecise in nature. Fuzzy linguistic variables are used to map the qualitative attributes. Finally, fuzzy based TOPSIS method is adopted to generate the ranking score of alternative suppliers. These ranking scores are used as input in a Multi-Choice Goal Programming (MCGP) model to determine optimal order allocation for respective suppliers. Finally, a sensitivity analysis assesses how the Supplier's Cost versus Resilience Index (SCRI) changes when differential priorities are set for respective cost and resilience attributes.
Innovation performance assessment of new products in a high-technology industry is conducive to assessing the quality of innovation. Therefore, it improves the operational efficiency of enterprises. It is of great significance for innovation policy-making. This paper presents a theoretical framework for evaluating innovation performance in which the contribution of new product development funds is divided into several elements, including invention, utility model, and appearance design patents. Based on this framework, the elasticity of invention patents to new product sales revenue is divided by the elasticity of new product development funds to new product sales revenue, and the result is used as an indicator to evaluate the innovation performance of new products. Taking the interprovincial panel data of China's high-technology industry as an example, the relationships between the variables, including number of invention patents, new product development funds, R&D funds, and new product sales revenue, were studied comprehensively by using a panel data simultaneous equation model, Granger causality tests, a panel threshold regression (PTR) model, and a Bayesian vector autoregressive (BVAR) model. The results showed that the overall innovation performance of new products in China's high-technology industry, which reached only 42.9%, was unsatisfactory. Despite the poor performance of invention patents, the high-technology industry in China showed strong developmental potential and is entering a transformation period for innovation quality improvement. The overall performance of investments in developing new products was satisfactory. The contribution of new product development funds increased as the enterprise scale increased and as new product sales revenue increased.
Turbulence is a crucial flow phenomenon for tidal energy converters (TECs), as it influences both the peak loads they experience and their fatigue life. To best mitigate its effects we must understand both turbulence itself and how it induces loads on TECs. To that end, this paper presents the results of blade element momentum theory (BEMT) simulations of flume-scale TEC models subjected to synthetic turbulent flows. Synthetic turbulence methods produce three-dimensional flowfields from limited data, without solving the equations governing fluid motion. These flowfields are non-physical, but match key statistical properties of real turbulence and are much quicker and computationally cheaper to produce. This study employs two synthetic turbulence generation methods: the synthetic eddy method and the spectral Sandia method. The response of the TECs to the synthetic turbulence is predicted using a robust BEMT model, modified from the classical formulation of BEMT. We show that, for the cases investigated, TEC load variability is lower in stall operation than at higher tip speed ratios. The variability of turbine loads has a straightforward relationship to the turbulence intensity of the inflow. Spectral properties of the velocity field are not fully reflected in the spectra of TEC loads.
It is well known that sustainability strategies have moved further and further up over the past decade due to help companies to improve the effectiveness of their marketplace and perform better in their operations. For companies, sustainability would gain long-term consequences such as getting greater profits and creating their own consumer path. The Triple Bottom Line (TBL) is a key element of the companies to achieve social, environmental, and economic benefits. Supplier's performance directly affects a company's performance not only environmental or economic issues but also sustainable issues. Thus, Sustainable Supplier Selection (SSS) has become the highly relevant topic and many authors and researchers have focused on this subject. This study investigates a hybrid multi-criteria decision making (MCDM) framework based on TBL to determine sustainable suppliers. After construction of hierarchy, the integrated fuzzy MCDM algorithm is implemented. At first, Fuzzy Analytical Hierarchy Process (FAHP) is used for obtaining the weights of the main criteria and related sub-criteria. Then, fuzzy TOPSIS method is applied for ranking the suppliers. Additionally, interval type-2 fuzzy sets (IT2FSs) that express uncertainty better than traditional type-1 fuzzy sets are used for selecting an appropriate supplier. The proposed approach is validated an actual case situation in Konya.
In this paper, we study the role of temporal coordination in managing the early stages of innovation (aka fuzzy front-end) in the context of virtual teams. Following a comparative case study approach, we detail the role of temporal coordination through the study of two contrasting virtual teams—one with a 24-h lifespan, and one with a five-month lifespan—from two Industry-Academia collaboration projects. Our approach was longitudinal capturing virtual team activities from start to end of each project, and involved multiple data collection methods, including observations and interviews. The findings reveal that the virtual team lifespan influences the type of temporal coordination that emerges. In virtual teams with short lifespans, with frequent communication can help to reduce the uncertainty characterizing the fuzzy front-end. On the other hand, in virtual teams with longer lifespans, allows dispersed members to work simultaneously on different, complementary aspects of the task at hand. These findings extend scholarly understanding around how innovation activities are coordinated in technology-mediated environments, such as virtual teams. Finally, we discuss theoretical and managerial implications.
This study offers a new perspective anchored in boundary theory on individuals’ life-puzzle (LP), especially the ones of women entrepreneurs in Sweden. This chapter is based on qualitative research. This chapter argues for a deeper understanding of work/non-work preferences for each boundary between life domains in order to comprehend the complexity of an individual’s life-puzzle as a combination of integration and segmentation at the service of their wellbeing. Findings show that women entrepreneurs in Sweden mostly develop blended LP composed of three domains: entrepreneurial work (EW), social, and family. EW combines the work and private domains as entrepreneurship is a way to align work activities with personal values and personal interest to stimulate higher needs in terms of sustainable society. The entrepreneurs’ LP is a result of integration and segmentation that complement each other. However, the range of blending/overlapping is greatly variated between individuals so that a zone of work-life reconciliation (ZWLR) is emerging. This chapter concludes that there is a zone of work-life reconciliation for entrepreneurs but that its size/shape/scope is contingent on the level of support for (women) entrepreneurship offered and perceived in time and place.
The introduction discusses the contemporary state of religion and spirituality in the helping professions, drawing on interdisciplinary research that examines both therapist and client experiences. Based on this analysis, it argues for a paradigm that respects the messiness of lived religion and spirituality (R/S), honors true pluralism, and can draw from a literature that crosses many models and disciplines. The Ways Paradigm is offered as such an approach that articulates three dimensions by which all helping models, regardless of their origins, can be understood and adapted to a wide range of clinical populations and presenting problems. This broad framework is used to tie together many strands of scholarship into R/S in counseling that cross disciplines and include the diverse manifestations of R/S in contemporary society. Using the Ways Paradigm as a template for integration, therapists will be able to deepen their knowledge, dispositions, and skills in R/S dimensions of therapy.
This chapter outlines an approach to explicit grammar instruction on the Chinese sentence-final le in the context of cognitive linguistics. From the perspective of prototype theory, this chapter demonstrates how the various sentence patterns of sentence-final le form a family of PERFECT constructions and show prototype effects. Building on Li et al. (1982), this chapter asserts that the most prototypical meaning of sentence-final le is to convey current relevant state, which is a state introduced by a prior eventuality and is relevant to the reference time. Traditionally, the explanation of sentence-final le in textbooks and pedagogical grammars rely heavily on the notion of change of state. This chapter further explores the discourse functions of change of state and its accessible definition for students of Chinese. This chapter proposes that the notions of currently relevant state and prior opposite state should be incorporated and emphasized in teaching sentence-final le. The former helps students understand the discourse functions of sentence-final le and the latter defines the meaning of change of state by the contrast between prior opposite state and currently relevant state. In addition, currently relevance should be treated as a graded notion. The more relevant and current the situation, the more likely a sentential le is used. Finally, this chapter showcases how to transform the linguistics descriptions into learner-friendly grammar instructions and suggests that the sequence of teaching sentence-final le constructions should be motivated by prototype effects. The most prototypical sentential le constructions should be introduced first and then the peripheral ones. Currently relevant state is also a conversational implicature inferred from the context. The chapter advises that Chinese language teachers should always provide scenarios of the currently relevant state when teaching sentence-final le so that students can better understand its discourse functions.