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GENETIC ALGORITHM BASED TRAIN SIMULATION USING CONCURRENT ENGINEERING

  • Type:Project
  • Chapters:5
  • Pages:30
  • Methodology:Nil
  • Reference:YES
  • Format:Microsoft Word
(Computer Science Project Topics & Materials)
ABSTRACT
To control the traffic during the data transmission with out any loss of packets using genetic algorithm. In this the packets are transferred by frames using mac layer. So Error correction can be easily done. Genetic algorithm based train simulation using concurrent engineering” control over a single wired lane network, the project proposes a technique to transfer the data from one place to another without traffic. The main aim of project is to control over traffic in a single wired lane network and multiple destination networks. This paper formulates an optimization framework for traffic controlled genetic algorithm in single wired networks with the constraint imposed by the mac. We develop a distributed, genetic algorithm controls congestion control scheme, which is shown to be stable in the absence of propagation delays, and allocates bandwidth to various users in a proportionally fair manner.
TABLE OF CONTENTS
CHAPTER ONE
1.0 INTRODUCTION
1.1 STATEMENT OF PROBLEM
1.2 AIMS AND OBJECTIVE
1.3 PURPOSE OF STUDY
1.4 SCOPE OF THE STUDY
1.5 LIMITATION OF THE STUDY
1.6 DEFINITION OF TERMS
CHAPTER TWO
2.0 LITERATURE REVIEW
CHAPTER THREE
3.0 METHODOLOGY FOR FACT FINDING AND DETAILED DISCUSSION OF THE SUBJECT MATTER
3.1 METHODOLOGY FOR FACT FINDING 
3.2 DETAILED DISCUSSION OF THE SUBJECT MATTER 
CHAPTER FOUR
4.0 THE FUTURE, IMPLICATIONS AND CHALLENGES OF THE SUBJECT MATTER FOR THE SOCIETY
4.1 THE FUTURE 
4.2 IMPLICATIONS
4.3 CHALLENGES OF THE SUBJECT MATTER FOR THE SOCIETY 
CHAPTER FIVE
5.0 SUMMARY, RECOMMENDATION AND CONCLUSION
5.1 SUMMARY 
5.2 RECOMMENDATION 
5.3 CONCLUSION 
REFERENCES
CHAPTER ONE
1.0 INTRODUCTION
This research addresses the issues to identify the optimal design of solid oxide fuel cell (SOFC) system considering functional performance and production cost. In this research modeling of the relations between design parameters and evaluation parameters is first discussed. Due to uncertainties of parameters relations, mathematical relations and neural network relations, and associate these two types of relations through a parameter relation network. The optimal SOFC system design considering function performance and production cost is achieved by changing values of design parameters based on evalustion of performance and cost parameters through multi-objectiv optimization. A software system has been developed based on the introduced method.
1.1 STATEMENT OF PROBLEM
Solid oxide fuel cell (SOFC) is a promising technology for power generation because of its high efficiency, low emission capability to operate with hydrocarbon fuels, rapid reaction kinetics, etc
1.2 AIMS AND OBJECTIVES
With the recent advance of the SOFC technology, SOFC systems are not only viable for large stationary power plants, but also possible as auxiliary power units for automobiles and cogeneration systems for residential use. 
To improve functional performance and reduce production cost more effective methods are required to model the SOFC systems and to identify the optimal design of SOFC systems.
1.3 PURPOSE OF STUDY
Despite the progress, poor performance and high cost are still the two major obstacles that prevent SOFC systems from commercialization.
1.4 SCOPE OF THE STUDY
Concurrent design is an approach to incorporate the considerations in down-stream product development life-cycle aspects such as manufacturing into the early design stage for shortening product development lead time reducing production cost and improving the overall design quality.
1.5 LIMITATION OF THE STUDY
Presently many methodologies and computer tools have been developed for solving concurrent design problems but most of the designs doesn’t rhymn with the project’s scope.
1.6 DEFINITION OF TERM
Solid oxide fuel cell – SOFC

GENETIC ALGORITHM BASED TRAIN SIMULATION USING CONCURRENT ENGINEERING

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Details

Type Project
Department Computer Science
Project ID CPU1205
Price ₦3,000 ($20)
Chapters 5 Chapters
No of Pages 30 Pages
Methodology Nil
Reference YES
Format Microsoft Word

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    Details

    Type Project
    Department Computer Science
    Project ID CPU1205
    Price ₦3,000 ($20)
    Chapters 5 Chapters
    No of Pages 30 Pages
    Methodology Nil
    Reference YES
    Format Microsoft Word

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