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Intelligent Traffic Management Using || AI & Metaheuristics || ~xRay Pixy

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Hybrid Artificial Intelligence and Metaheuristics for Smart City TRafci Management Problem Video Chapters: 00:00 Introduction 00:40 Smart Cities 01:14 Traditional Methods for Traffic Management 02:12 Hybrid Approach AI and Metaheuristics 02:47 STEPS for Hybrid  Traffic Management System 08:40 Advantages of Smart Traffic Management System 09:33 Conclusion
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Software Engineering

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 Software Engineering 

Software Engineering: Software Engineering (S.E.) is a profession dedicated to the designs, implementation, and modification of software. Applications of Software Engineering are: 
  1. Re-engineering of software
  2. Software Testing
  3. Software Maintainance 
  4. Software Analysis
  5. Software Design
  6. Software Implementation
The objective of software engineering is to produce good quality software, on time and within budget. To obtain this objective it is very important to focus on Software Quality and Software Development Process.
Software Characteristics are: 
  1. Reusability of the components.
  2. Softwares are not manufactured as hardware. 
  3. In the Software development process, there is no wear-out phase.
  4. Software is fixable.
Software Life Cycle Models: Software life cycle means the time period when a software product is conceived and when the software product is no longer available for use. The software Life cycle includes different phases:
  1. Requirement Phase
  2. Design Phase
  3. Implementation Phase
  4. Testing Phase
  5. Installation Phase
  6. Operation and Maintenance Phase
  7. Retirement Phase 
Software Requirement - > Software Design - > Software Implementation - > Software Testing - > Software Installation - > Software Maintenance - > Software Retirement. 

Software life cycle models in software engineering are often known as Software Development Life cycle (S.D.L.C). Different software life cycle models are:
  1. The Waterfall Model
  2. Increment Process Models
  3. Evolutionary Process Model
  4. Prototyping Model
  5. Spiral Model
  6. COCOMO Model - Constructive Cost Estimation Model
COCOMO Model: COCOMO (Constructive Cost Estimation Model) is a heuristic estimation technique proposed by Boehm. According to Bohem, there are 3 categories for software development based on development complexity: 
  1. Organic - Application. 
  2. Semidetached - Utility.
  3. Embedded - System Programs.
Software cost estimation should be done through 3 stages: Basic COCOMO, Intermediate COCOMO, and Complete COCOMO. COCOMO models are useful for project Time and Cost estimation. 







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PARTICLE SWARM OPTIMIZATION ALGORITHM NUMERICAL EXAMPLE

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Cuckoo Search Algorithm for Optimization Problems

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PSO Python Code || Particle Swarm Optimization in Python || ~xRay Pixy

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Bat algorithm Explanation Step by Step with example

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Grey Wolf Optimization Algorithm

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how is the LBP |Local Binary Pattern| values calculated? Step-by-Step with Example

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Grey Wolf Optimization Algorithm Numerical Example

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Whale Optimization Algorithm Code Implementation || WOA CODE || ~xRay Pixy

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