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Stock market identification and forecasting are highly complex in terms of mathematical modeling due to the complexity of internal structure and external forces that contributes the nonlinear dynamics of its behaviors. In this paper, fuzzy system is used to identify the stock market and produce the parameters to estimate the closing price of the selected stock market. Due to the abilities of incorporating...
This paper presents the architecture and working principles of a Decision Support System (DSS) for logistics networks. The system relies on a data-driven discrete-event simulation model. A brief introduction to Reinforcement Learning (RL) and an explanation of the adoption of RL to the concepts of the DSS is given. An illustration of the realization is presented using a specific aspect of a logistics...
This paper measures marketing ability and financial performance and examines what cause the overall operations inefficiency based on the operational process decomposition. The empirical research on e-portal and e-commerce company show that e-portal company has better marketing ability while e-commerce firm has better financial performance. For e-commerce company, it is marketing ability conversion...
Consumer-oriented companies can no longer afford to make decisions or measure results based on gut feeling. They must be able to take advantage of all available data. Advanced analytics makes it possible to capture value and benefit from big data, however, this isn't a given. Companies must hire, develop, and retain skilled analysts, who can distinguish relevant from irrelevant data, draw the right...
We propose a novel approach for predicting Web user click intention, using pupil dilation data generated by an eye-tracking device as input. Our goal is to determine if this variable is useful to differentiate choice and no-choice states, and if so, to generate a classification model for predicting choice understood as a click. For this, we performed an experiment with 25 healthy subjects in which...
Small and medium-sized enterprises play a very important role in China's economic and social development. Their development is inseparable from the financial support, and the development of credit business is also an important aspect of bank's operation. At the time of solving the problem of financing difficulties of small and medium-sized enterprises, how to manage credit risk will become an important...
Today's supply chain (SC) is highly complex and inter-connected so disruption at one company can propagate to other companies in an unexpected manner. However, most approaches in the area of risk management provide only static analysis of the SC risk but not the propagation of disruption through the SC network. Thus, in this paper, we propose a time-based model that quantifies the magnitude of the...
This paper describes a decision support system (DSS) built on knowledge extraction using simulation-based optimization and data mining. The paper starts with a requirements analysis based on a survey conducted with a number of industrial companies about their practices of using simulations for decision support. Based upon the analysis, a new, interactive DSS that can fulfill the industrial requirements,...
Simulation-based optimisation is popularly employed to determine the best system configuration of complex simulation models. However, it is assumed that the input distribution and parameters are known. In this paper, the input distribution parameter is assumed to be unknown and the impact of the same on the optimal system configurations obtained is investigated. Bootstrapping of the sample data is...
A novel short-wave passive location algorithm based on radial basis function neural networks (RBFNN) is proposed. Using the RBFNN's characteristic of approximating any continuous nonlinear function, the fusion of electromagnetic spectrum sensing data is realized by sample learning. And the mapping model of short-wave monitoring data, detecting data and targets' position information is constructed...
As Twitter usage increases worldwide, it becomes an important part of the big data ecosystem. People from across the globe tweeting and retweeting a large number of tweets instantaneously results in exponential growth of the information diffusion. This in turn can cause information bubbles. As data from Twitter and other microblogs are used in predictive analytics in many areas such as stock price...
Due to advancement of social network and popularization of mobile devices, the existing relational database management system(RDBMS)'s processing of massive data has become an issue. NoSQL is a database management system which makes processing of massive and/or unstructured data easier, and many companies today tend to start a project using NoSQL. Moreover, converting the RDBMS of current systems...
As ERP was believed to provide a lot promising benefits, many companies try to implement it in their business processes. By implementing ERP, they expect to get those promised benefits. In fact, although many companies have successfully implemented ERP systems, not all companies get the benefits of ERP system since ERP systems have not been able to diffuse in the routine of the organizations. A lot...
Modern organizations face the challenge of constantly evolving skills and an ever-changing demand for products and services. In order to stay relevant in business, they need their workforce to be proficient in the skills that are in demand. This problem is exacerbated for large organizations with a complex workforce. In this paper, we propose a novel, analytics-driven approach to help organizations...
The authors introduce a growth model of the circulation of a stock and flow process that makes use of stock as an important factor in designing a data marketplace. The model highlights the necessity of considering how learning efficiency must be designed for the purpose of concept design. The model is applied to a business case in commercial industry to discuss the essentials of stock and learning...
This paper reports on a case study that was conducted in a cloud High Performance Computing (HPC) project one that used very sensitive and confidential data. The study aimed to explore the security challenges and practicalities that occur within a cloud HPC project and to develop a method for making critical security decisions. Action research was used to examine the nuances throughout the project...
Patent data has been used for generating patent-based indicators for tracking the technology development of high-tech companies. In this paper, we further show the promises of exploiting patent data for the analysis and prospecting of high-tech companies in the stock market. Specifically, we aim at investigating the relationship between the patent activities of high-tech companies and the dynamics...
The advent of social networks and Internet-of-Things has resulted in unprecedented capability of collecting, sharing and analyzing massive amounts of data. From a security perspective, Big Data may seriously weaken confidentiality, as techniques for improving Big Data analytics performance-including early fusion of heterogeneous data sources — increase the hidden redundancy of data representation,...
In recent years, the widespread adoption of GPS enabled vehicles brings the Location Based Services new opportunities. It benefits many related fields such as urban planning, city traffic modeling, personalized recommendations and driving suggestions. The service providers can understand their users better by modeling the mobility pattern and provide more personalized services by predicting the destination...
Modern organizations invest a lot of resources in recruiting, managing, and retaining people with high value and talent. In spite of several studies over the past fifty years, there is no silver bullet for talent management, since the area itself is constantly evolving due to the ever-changing nature of the enterprise in the knowledge economy. In this paper, we adopt an analytics-based approach to...
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