1. INTRODUCTION

In this section we present genetic programming, being the fourth member of the evolutionary algorithm family. Besides the particular representation (using trees as chromosomes) it differs from other EA strands in its application area. While the EAs are typically applied to optimization problems, GP could be rather positioned in machine learning. In terms of nature of this deferent problem types, most other EAs are used for finding some input realizing maximum payoff, whereas GP is used to seek models with maximum fit. Clear ....etc

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i need ppt about this paper...genetic programming approach to record deduplication about existing and proposed ....etc

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NC and CNC machines and Control Programming




Motivation and uses


To manufacture complex curved geometries in 2D or 3D was extremely expensive by mechanical means (which usually would require complex jigs to control the cutter motions)


Machining components with repeatable accuracy


Advantages of CNC

Easier to program;
- Easy storage of existing programs;
- Easy to change a program
- Avoids human errors
- NC machines are s ....etc

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NC and CNC machines and Control Programming


History of CNC


1949
US Air Force asks MIT to develop a numerically controlled machine.

1952
Prototype NC machine demonstrated (punched tape input)


1980-
CNC machines (computer used to page link directly to controller)


1990-
DNC: external computer “drip feeds” control programmer to machine tool controller
....etc

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Genetic programming (GP) is an automated methodology inspired by biological evolution to find computer programs that best perform a user-defined task. It is therefore a particular machine learning technique that uses an evolutionary algorithm to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task. The first experiments with GP were reported by Stephen F. Smith (1980) and Nichael L. Cramer (1985), as described in the famous book Genetic Programming: O ....etc

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Genetic programming (GP) is an automated methodology inspired by biological evolution to find computer programs that best perform a user-defined task. It is therefore a particular machine learning technique that uses an evolutionary algorithm to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task. The first experiments with GP were reported by Stephen F. Smith (1980) and Nichael L. Cramer (1985), as described in the famous book Genetic Programming: O ....etc

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Genetic programming (GP) is an Automated Methodology

Genetic programming (GP) is an automated methodology inspired by biological evolution to find computer programs that best perform a user-defined task. It is therefore a particular machine learning technique that uses an evolutionary algorithm to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task.

The first experiments with GP were reported by Steph ....etc

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Genetic programming (GP) is an automated methodology inspired by biological evolution to find computer programs that best perform a user-defined task. It is therefore a particular machine learning technique that uses an evolutionary algorithm to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task. The first experiments with GP were reported by Stephen F. Smith (1980) and Nichael L. Cramer (1985), as described in the famous book Genetic Programming: O ....etc

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ABSTRACT
Genetic programming (GP) is an automated method for creating a working computer program from a high-level problem statement of a problem.
Starting with a primordial ooze of thousands of randomly created computer programs, a population of programs is progressively evolved over a series of generations. The evolutionary search uses the Darwinian principle of survival of the fittest and is patterned after naturally occurring operations, including crossover (sexual recombination), mutation, gene duplication, gene deleti ....etc

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GENETIC PROGRAMMING A SEMINAR REPORT
Submitted by
GAURAV AHUJA
COMPUTER SCIENCE & ENGINEERING
SCHOOL OF ENGINEERING
COCHIN UNIVERSITYUNIVERSITY OF SCIENCE &
TECHNOLOGY, KOCHI-682022

ABSTRACT
Genetic programming (GP) is an automated methodology inspired by biological evolution to find computer programs that best perform a user- defined task. It is therefore a particular machine learning technique that use ....etc

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