Search results
Results from the WOW.Com Content Network
Fuzzy cognitive maps are signed fuzzy directed graphs. Spreadsheets or tables are used to map FCMs into matrices for further computation. FCM is a technique used for causal knowledge acquisition and representation, it supports causal knowledge reasoning process and belong to the neuro-fuzzy system that aim at solving decision making problems, modeling and simulate complex systems. [4]
[6] [7] [8] These tutorial articles remain useful today, but the primary reference for usage is the 1927 Abney Level Handbook. [3] The Abney level is typically used at the eye height of the surveyor, either hand-held or mounted on a staff at that height. To measure lines on a particular slope, the desired angle or grade is first set on the ...
Published by Dan Gillespie in 1977, and is a linear search on the cumulative array. See Gillespie algorithm . Gillespie’s Stochastic Simulation Algorithm (SSA) is essentially an exact procedure for numerically simulating the time evolution of a well-stirred chemically reacting system by taking proper account of the randomness inherent in such ...
The PCR method may be broadly divided into three major steps: 1. Perform PCA on the observed data matrix for the explanatory variables to obtain the principal components, and then (usually) select a subset, based on some appropriate criteria, of the principal components so obtained for further use.
Example of a Nassi–Shneiderman diagram. A Nassi–Shneiderman diagram (NSD) in computer programming is a graphical design representation for structured programming. [1] This type of diagram was developed in 1972 by Isaac Nassi and Ben Shneiderman who were both graduate students at Stony Brook University. [2]
A Gantt chart is a type of bar chart [4] [5] that illustrates a project schedule. [6] This chart lists the tasks to be performed on the vertical axis, and time intervals on the horizontal axis.
Statistica is a suite of analytics software originally developed by StatSoft and acquired by Dell in March 2014. The software includes an array of data analysis, data management, data visualization, and data mining procedures; as well as a variety of predictive modeling, clustering, classification, and exploratory techniques. [2]
The primary application of the Levenberg–Marquardt algorithm is in the least-squares curve fitting problem: given a set of empirical pairs (,) of independent and dependent variables, find the parameters of the model curve (,) so that the sum of the squares of the deviations () is minimized: