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Big data analytics is defined as technologies (database and data mining tools) and techniques (analytical methods) that a company can implement to analyse large scale, complex data for various applications intended to augment the performance of the firm in various dimensions.
To do this it makes use of statistical analysis techniques, analytical queries and automated machine learning algorithms.
Solutions have been defined by making collaborate different diagnosis techniques (analytical redundancy, consistency based approach, model checking and Hinf estimator) from several origins, locally in each component.
The major themes include advancements in data collection techniques, analytical and modeling methods, and simulation applications which provide insights into behavior energy savings potential and impact.
To achieve this, the study compares the results of two quantitative techniques (analytical hierarchy procedure (AHP) and Fuzzy AHP) in defining the extent of land-use zones at a large scale urban planning scenario.
The basic principles of characterization including physisorption, chemisorption, temperature-programmed techniques, X-ray techniques, analytical electron microscopy, and vibrational spectroscopies, are all drivers for development of a complete collage or suite of physiochemical properties, important for structure-property-performance relationships.
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The techniques of analytical chemistry are relied on heavily to maintain a benign environment.
Reliable principles of Shakespearean editing have begun to emerge only with modern developments in the techniques of analytical bibliography.
The laboratory work is mainly an application of the techniques of analytical science.
Positron emission tomography (PET) imaging techniques offer analytical approaches for examining neuroreceptor systems.
As-received NDs were characterized by a series of spectroscopy techniques and analytical methods.
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