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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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Vitamin B12 Deficiency: Symptoms, and Foods for Vegetarians

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 Vitamin B12 - Health Care

 Vitamin B12 Deficiency Symptoms

  1.  Pale Skin
  2.  Weakness
  3.  Dizziness
  4.  Depression
  5.  Vision Loss / Blurred Vision
  6.  Memory Loss
  7.  Depression
  8.  Mental Issues
  9.  Confusion
  10.  Gas
  11.  Short of breath
  12.  Constipation
  13.  Diarrhea
  14.  Loss of Appetite
  15.  Behavior Change

Vitamin b12 foods For Vegetarians

Vitamin B12 Rich Fruits

  • Apple
  • Mango
  • Orange
  • Banana
  • Blueberries
  • Beetroots

Vitamin B12 Rich Dry Fruits

  • Nuts
  • Almonds
  • Peanuts
  • Dates
  • Walnuts
  • Hazelnuts
  • Pistachios
  • Macadamia Nuts
  • Cashews
  • Apricots
  • Popcorn

Vitamin B12 Rich Vegitables 

  • Potato
  • Fermented Soybeans
  • Alfa Alfa
  • Mushrooms

Vitamin B12 Rich Dairy Products

  • Milk
  • Butter
  • Cheese
  • Yogurt
-----------------------------------HEALTH IS WEALTH------------------------------------------------------------








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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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Particle Swarm Optimization Implementation in Python Video Chapters: 00:00 Introduction 02:01 Code 05:55 Position Initialization 08:06 PSO Main Loop 08:42 Velocity Calculation 10:02 Position Update 10:36 Fitness Evaluation 13:21 Objective Function 17:44 Result 19:00 Conclusion .....................................................SOURCE CODE......................................................................... import random import numpy as np from tkinter import messagebox #Define Class Particles class Particle: def __init__ (self,position): self.position=position self.velocity=np.zeros_like(position) self.best_position=position self.best_fitness=float('inf') def PSO(ObjF,Pop_Size,D,MaxT): swarm_best_position=None swarm_best_fitness=float('inf') particles=[] #Posotion Initialization position=np.random.uniform(-0.5,0.5,D) particle=Particle(position) particles.append(particle) #Fit
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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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 Grey Wolf Optimization Algorithm Numerical Example Grey Wolf Optimization Algorithm Steps 1.) Initialize Grey Wolf Population. 2.) Initialize a, A, and C. 3.) Calculate the fitness of each search agent. 4.) 𝑿_𝜶 = best search agent 5.) 𝑿_𝜷 = second-best search agent 6.) 𝑿_𝜹 = third best search agent. 7.) while (t<Max number of iteration) 8.) For each search agent       update the position of the current search agent by the above equations end for 9.) update a, A, and C 10.) Calculate the fitness of all search agents. 11.) update 𝑿_𝜶, 𝑿_𝜷, 𝑿_𝜹 12.) t = t+1 end while 13.) return 𝑿_𝜶 Grey Wolf Optimization Algorithm Numerical Example STEP 1.  Initialize the Grey wolf Population [Initial Position for each Search Agent] 𝒙_(𝒊  )  (i = 1,2,3,…n)     n = 6 // Number of Search Agents  [ -100, 100] // Range Initial Wolf Position      3.2228     4.1553    -3.8197     4.2330     1.3554    -4.1212 STEP 2. Calculate Fitness for Each Search Agent.    Objective Function: F6(x)  = su
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Whale Optimization Algorithm Code Implementation || WOA CODE || ~xRay Pixy

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