Computing statistical indices for hydrothermal times using weed emergence data
نویسندگان
چکیده
منابع مشابه
Computing statistical indices for hydrothermal times using weed emergence data
R. CAO, M. FRANCISCO-FERNÁNDEZ*, A. ANAND, F. BASTIDA AND J. L. GONZÁLEZ-ANDÚJAR 1 Faculty of Computer Science, Department of Mathematics, Campus de Eviña, s/n, A Coruña 15071, Spain Department of Mathematics, Indian Institute of Technology, Kharagpur 721302, India Polytechnic School, Department of Agroforestry Science, University of Huelva, Campus Universitario de La Rábida, Carretera de Palos...
متن کاملInvestigating electrochemical drilling (ECD) using statistical and soft computing techniques
In the present study, five modeling approaches of RA, MLP, MNN, GFF, and CANFIS were applied so as to estimate the radial overcut values in electrochemical drilling process. For these models, four input variables, namely electrolyte concentration, voltage, initial machining gap, and tool feed rate, were selected. The developed models were evaluated in terms of their prediction capability with m...
متن کاملA SIMPLE ALGORITHM FOR COMPUTING TOPOLOGICAL INDICES OF DENDRIMERS
Dendritic macromolecules’ have attracted much attention as organic examples of well-defined nanostructures. These molecules are ideal model systems for studying how physical properties depend on molecular size and architecture. In this paper using a simple result, some GAP programs are prepared to compute Wiener and hyper Wiener indices of dendrimers.
متن کاملStatistical Computing Methods for Imaging Data Processing
Many high dimensional data sets such as imaging mass spectrometry (IMS) and functional magnetic resonance imaging (fMRI) data are of the hyper-spectral imaging (HSI) type. Advanced mathematical tools and statistical techniques not only provide significance analysis of experimental data sets but also can help in finding new data features/patterns, guiding biological experiments designs, as well ...
متن کاملData structures for statistical computing in Python
In this paper we are concerned with the practical issues of working with data sets common to finance, statistics, and other related fields. pandas is a new library which aims to facilitate working with these data sets and to provide a set of fundamental building blocks for implementing statistical models. We will discuss specific design issues encountered in the course of developing pandas with...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Journal of Agricultural Science
سال: 2011
ISSN: 0021-8596,1469-5146
DOI: 10.1017/s002185961100030x