نتایج جستجو برای: fuzzy just excel lent

تعداد نتایج: 247986  

Journal: :Computational Statistics & Data Analysis 2005
Leo Knüsel

Some of previously indicated errors in Microsoft Excel 97 and Excel XP have been eliminated in Excel 2003. But some others have not been corrected in Excel 2003 and new ones have been found as is shown by numerical examples.

Journal: :Anais da Academia Brasileira de Ciencias 2005
José Jurberg

Brazil and Science lost a unique figure on July 7, 2004, when Herman Lent died, at 93 years of age. Herman Lent was Emeritus Researcher of the Fundação Oswaldo Cruz, recipient of the Order of Scientific Merit in the category of Grã-Cruz in 2002, Member ofAcademia Brasileira de Ciências (Brazilian Academy of Sciences) and Lecturer and Researcher level 1A of Conselho Nacional de Desenvolvimento C...

2009
Joanna Page

! motivate the question. What is at stake here? Why is this such a significant question? Is it an area of controversy? ! introduce the material you will be using to answer the question (e.g. text[s]), if not defined by the question. ! define the terms of the question if necessary, and/or problematise these if relevant. ! give relevant context for the specific material you will be focusing on. I...

2001
Patricia A. Wilson A. WILSON

Social capital creates local economic prosperity. This ® nding by Putnam (1993a), Fukuyama (1995), Coleman (1988, 1990) and other social scientists has lent legitimacy to what those involved in community economic development have known intuitively for years: the level of inter-personal trust, civic engagement and organisational capability in a community counts. Their research indicates that the...

2016
Jagannath E. Nalavade T. Senthil Murugan

Data stream; Neuro fuzzy; Change of detection; Rough set theory; Holoentropy function Abstract Data stream classification plays a vital role in data mining techniques which extracts the most important patterns from the real world database. Nowadays, many applications like sensor network, video surveillance and network traffic generate a huge amount of data streams. Due to the ambiguity in input...

2014
Tejwant Singh Manish Mahajan

Fuzzy C-Mean (FCM) is an unsupervised clustering algorithm based on fuzzy set theory that allows an element to belong to more than one cluster. Where fuzzy means “unclear” or “not defined” and c denotes “clustering”. In FCM the number of cluster are randomly selected. [15] FCM is the advanced version of K-means clustering algorithm and doing more work than K-means. K-Means just needs to do a di...

Purpose: Making use of the quantitative method of data envelopment analysis (DEA), this research tries to calculate the efficiency and ranking of public libraries in Iranian provinces in 2008. Methodology: This research is an applied study and was conducted as survey. Data collection was performed from internet. The time interval of the used data was the year 2008 and data were classified with...

2016

This book is meant to be read and used by professors and economists. It assumes familiarity with economic theory and data analysis, so it will not make sense to a student or beginner. It is a manual for utilizing teaching materials that are available on the Web at http://www.depauw.edu/learn/ macroexcel. It is assumed that the professor has a favorite textbook or readings that neither this book...

Journal: :Computer methods and programs in biomedicine 2007
Margarida Rocheta F. Miguel Dionísio Luís Fonseca Ana M. Pires

Paternity analysis using microsatellite information is a well-studied subject. These markers are ideal for parentage studies and fingerprinting, due to their high-discrimination power. This type of data is used to assign paternity, to compute the average selfing and outcrossing rates and to estimate the biparental inbreeding. There are several public domain programs that compute all this inform...

1992
Detlef Nauck Rudolf Kruse

In this paper we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work in 2]. We solve this problem by deenining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy err...

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