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Save my name, email, and website in this browser for the next time I comment. Sign in. Forgot your password? Get help. Privacy Policy. Password recovery. Different types of data used in AI development. Top features of best GPS tracking systems. In this paper we will address this question by means of a In this paper we will address this question by means of a new procedure, which we call Nonlinear Discriminant Analysis NLDA , for classifier construction in such cases and that combines the excellent approximation properties of.
The forecasting model The forecasting model includes automobile sales, automobile price, Euro and Dollar exchange rate, employment rate, consumer confidence index, oil prices and industrial production confidence index, the probability of buying an automobile, female employment rate, general economic situation, the expectation of general economic situation, financial status of households, expectation of financial status of households.
According to the regression results, changes in Dollar exchange rate, the expectation of financial status of households, seasonally adjusted industrial production index, logarithmic form of automobile sales before-one-month which have a significant effect on automobile sales, are found to be the significant variables. The results show that ANN has a better estimation While the topic of analytics is rapidly growing in popularity across various domains, there is still a relatively low amount of empirical work in the field of operations research.
While studies of various technical and business aspects of While studies of various technical and business aspects of analytics are emerging in OR, little has been done to address how the OR community can leverage business analytics in dynamic and uncertain environments — the very place where OR is supposed to play a key role.
To address this gap, this study draws on the dynamic capabilities view of the firm and builds on eight selected case studies of operations research activity in large organisations, each of whom have invested significantly in analytics technology and implementation.
The study identifies fourteen analytics-enabled microfoundations of dynamic capabilities, essentially highlighting how organisations can use analytics to manage and enhance their OR activities in dynamic and uncertain environments.
This study also identifies six key crosscutting propositions emerging from the data and develops a roadmap for future OR researchers to address these issues and improve the use and value of analytics as enablers of organisational dynamic capabilities. Related Topics. Business Intelligence. Follow Following. Big Data Analytics. Clickstream Analysis. Mathematics and Physics. Flow Shop Scheduling. Predictive Analytics. Cost of Acquistion. Manufacturing Planning and Control Systems.
Ads help cover our server costs. Log in with Facebook Log in with Google. Remember me on this computer. Enter the email address you signed up with and we'll email you a reset link. Need an account? Click here to sign up. It will motivate researchers to address these issues of storage, management, and retrieval of data known as Big Data. As well as the usages of Big Data analytics in India is also highlighted.
A survey of big data architectures and machine learning algorithms in healthcare. Big Data has gained much attention from researchers in healthcare, bioinformatics, and information sciences.
As a result, data production at this stage will be 44 times greater than that in Hence, the volume, velocity, and variety Hence, the volume, velocity, and variety of data rapidly increase. Hence, it is difficult to store, process and visualise this huge data using traditional technologies. Many organisations such as Twitter, LinkedIn, and Facebook are used big data for different use cases in the social networking domain.
Also, implementations of such architectures of the use cases have been published worldwide. However, a conceptual architecture for specific big data application has been limited.
The intention of this paper is application-oriented architecture for big data systems, which is based on a study of published big data architectures for specific use cases. This paper also provides an overview of the state-of-the-art machine learning algorithms for processing big data in healthcare and other applications. Health data analytics using scalable logistic regression with stochastic gradient descent. Nisso reside, ainda, problema para pesquisa. Enhancing energy awareness through the analysis of thermal energy consumption.
Energy efficiency by means of reduction in wasteful energy consumption is a growing policy priority for many countries.
Innovative systems should be designed to continuously monitor a smart city environment and provide all stakeholders Innovative systems should be designed to continuously monitor a smart city environment and provide all stakeholders the tools to improve energy efficiency. This paper presents the EDEN platform, designed to collect and analyze thermal energy consumption of residential and public building heating systems. EDEN is being deployed in a major Italian city and collects energy consumption measurements through an extensive smart metering grid involving thousands of buildings.
EDEN also collects and analyzes indoor climate conditions, and user feedbacks, such as their thermal comfort perception, by means of an ad-hoc social network. Collected data are further enriched with temporal and spatial information at different abstraction levels and meteorological data available as an open source data set. Related Topics. Big Data. Follow Following.
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