Data Mining in Agriculture by Antonio Mucherino

By Antonio Mucherino

Data Mining in Agriculture represents a complete attempt to supply graduate scholars and researchers with an analytical textual content on facts mining strategies utilized to agriculture and environmental comparable fields. This e-book offers either theoretical and useful insights with a spotlight on offering the context of every info mining process quite intuitively with considerable concrete examples represented graphically and with algorithms written in MATLAB®.

Examples and workouts with ideas are supplied on the finish of every bankruptcy to facilitate the comprehension of the fabric. for every facts mining procedure defined within the booklet editions and enhancements of the fundamental set of rules also are given.

Also through P.J. Papajorgji and P.M. Pardalos: Advances in Modeling Agricultural Systems, 'Springer Optimization and its purposes' vol. 25, ©2009.

Show description

Read Online or Download Data Mining in Agriculture PDF

Best linear programming books

Integer Programming: Theory and Practice

Integer Programming: thought and perform includes refereed articles that discover either theoretical facets of integer programming in addition to significant functions. This quantity starts with an outline of recent confident and iterative seek tools for fixing the Boolean optimization challenge (BOOP).

Extrema of Smooth Functions: With Examples from Economic Theory

It isn't an exaggeration to country that almost all difficulties handled in financial idea might be formulated as difficulties in optimization concept. This holds precise for the paradigm of "behavioral" optimization within the pursuit of person self pursuits and societally effective source allocation, in addition to for equilibrium paradigms the place life and balance difficulties in dynamics can usually be said as "potential" difficulties in optimization.

Variational and Non-variational Methods in Nonlinear Analysis and Boundary Value Problems

This ebook displays an important a part of authors' learn task dur­ ing the final ten years. the current monograph is developed at the effects received via the authors via their direct cooperation or because of the authors individually or in cooperation with different mathematicians. most of these effects slot in a unitary scheme giving the constitution of this paintings.

Optimization on Low Rank Nonconvex Structures

International optimization is without doubt one of the quickest constructing fields in mathematical optimization. in truth, more and more remarkably effective deterministic algorithms were proposed within the final ten years for fixing numerous sessions of huge scale particularly established difficulties encountered in such parts as chemical engineering, monetary engineering, situation and community optimization, creation and stock regulate, engineering layout, computational geometry, and multi-objective and multi-level optimization.

Additional resources for Data Mining in Agriculture

Example text

The acceptance strategy usually used is based on the Metropolis acceptance function [164]. 5 Data mining and agriculture 19 t = t0 maxout = maximum allowed number of outer iterations nsteps = number of steps at constant temperature X = random starting solution nout = 0 while (f (X) not stable and nout ≤ maxout) nout = nout + 1 for k = 1, nsteps X(k) = random perturbation on X p = uniform random number in (0,1) if (A(X,X(k),t)) > p) then X = X(k) end if end for t = γ t, γ < 1 end while Fig. 4 The simulated annealing algorithm.

By applying interpolation or regression techniques, the hope is to find a function that is able to describe this phenomenon or process in general. Let us suppose that the quantity of water y in a certain soil is monitored during time x. Experimental analysis can be used for obtaining y at different times x, so that a set of points (x , y ) can be defined. As always in real life applications, the number of experiments is discrete and limited, whereas a general function able to relate each time x to a water level y is searched.

For more details about validation techniques, refer to Chapter 8. 3 Mining market data Data mining applied to finance is also referred to as financial data mining. Some of the most recent papers on this topic are [240], in which a new adaptive neural network is proposed for studying financial problems, and [247], in which stock market tendency is studied by using a support vector machine approach. In fact, in finance, one of the most important problems is to study the behavior of the market. The large number of stock markets provides a considerable amount of data every day in the United States only.

Download PDF sample

Rated 4.52 of 5 – based on 21 votes