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Section 4.3
... From the chart in the solution to Example 1, we see that f '(x) changes from negative to positive at -1. So, f(-1) = 0 is a local minimum value by the First Derivative Test. ...
... From the chart in the solution to Example 1, we see that f '(x) changes from negative to positive at -1. So, f(-1) = 0 is a local minimum value by the First Derivative Test. ...
Evolving Neural Networks using Ant Colony Optimization with
... weights to the BP in order to perform a local search improvement. It was also suggested that in problems where heuristic information is not available, ACO needs to be applied with a local search scheme. In fact, training an ANN is one of these problems because it is not possible to consider the valu ...
... weights to the BP in order to perform a local search improvement. It was also suggested that in problems where heuristic information is not available, ACO needs to be applied with a local search scheme. In fact, training an ANN is one of these problems because it is not possible to consider the valu ...
Mathematical optimization
In mathematics, computer science and operations research, mathematical optimization (alternatively, optimization or mathematical programming) is the selection of a best element (with regard to some criteria) from some set of available alternatives.In the simplest case, an optimization problem consists of maximizing or minimizing a real function by systematically choosing input values from within an allowed set and computing the value of the function. The generalization of optimization theory and techniques to other formulations comprises a large area of applied mathematics. More generally, optimization includes finding ""best available"" values of some objective function given a defined domain (or a set of constraints), including a variety of different types of objective functions and different types of domains.