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Bermuda Triangle Optimizer

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VIDEO LINK The Bermuda Triangle Optimizer (BTO) is a nature-inspired algorithm that simulates a gravity-like pull in the Bermuda Triangle to find optimal solutions. Learn Bermuda Triangle Optimizer (BTO) Step-By-Step using Examples. Video Chapters: Bermuda Triangle Optimizer (BTO) 00:00 Introduction 00:34 About the Bermuda Triangle 02:06 Bermuda Triangle Optimizer  05:44 BTO STEPS 09:30 BTO Advantages 10:17 BTO Limitations 10:42 BTO Applications 11:07 Conclusion Bermuda Triangle Optimizer || Step-By-Step || ~xRay Pixy Video Link:  https://youtu.be/bBnsd7BBttg #optimization #algorithm #metaheuristic #robotics #deeplearning #ArtificialIntelligence #MachineLearning #computervision #research #projects #thesis #Python #optimizationproblem #optimizationalgorithms 
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JavaScript Analog Clock || Step-By-Step || ~xRay Pixy

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---------------------------- clock.html ---------------------------------------

<html>
<head>
<title>Javascript Analog Clock</title>
<link rel ="stylesheet" href="clock.css">
<script src = "clock.js"></script>
</head>
<body>
<div id="clockBox">
     <div id="hour"></div>
     <div id="minute"></div>
     <div id="second"></div>
     <div id="point"></div>
</div>
</body>
</html>


------------------------------ clock.css -----------------------------------------
#clockbox{
          height: 650px;
          width: 650px;
          background: url(clc.png);
          background-size:100%;
          margin:auto;
       
}
#hour, #minute, #second{
                        position:absolute;
                        background:red;
                        border-radius:15px;
                        transform-origin:bottom;
}

#hour{
                        width:1.6%;
                        height:25%;
                        left:48.85%;
                        top: 25%;
                        
}
#minute{
                        width: 1.4%;
                        height:30%;
                        left: 48.9%;
                        top:18%;
                        
}

#second{
                        width:0.8%;
                        height:36%;
                        top: 9%;
                        left: 49.25%;
                          
}

              
---------------------------- clock.js ---------------------------------------------------

setInterval(() => {
                       D = new Date();
                       H = D.getHours();
                       M = D.getMinutes();
                       S = D.getSeconds();
                       
                       H_rotation = 30 * H + M / 2;
                       M_rotation = 6 * M;
                       S_rotation = 6 * S;
                       
                       hour.style.transform =`rotate(${H_rotation}deg)`;
                       minute.style.transform =`rotate(${M_rotation}deg)`;
                       second.style.transform =`rotate(${S_rotation}deg)`;
                     
},1000);

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PARTICLE SWARM OPTIMIZATION ALGORITHM NUMERICAL EXAMPLE

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 Particle swarm optimization (PSO) What is meant by PSO? PSO is a computational method that Optimizes a problem. It is a Population-based stochastic search algorithm. PSO is inspired by the Social Behavior of Birds flocking. n Particle Swarm Optimization the solution of the problem is represented using Particles. [Flocking birds are replaced with particles for algorithm simplicity]. Objective Function is used for the performance evaluation for each particle / agent in the current population. PSO solved problems by having a Population (called Swarms) of Candidate Solutions (Particles). Local and global optimal solutions are used to update particle position in each iteration. How PSO will optimize? By Improving a Candidate Solution. How PSO Solve Problems? PSO solved problems by having a Population (called Swarms) of Candidate Solutions (Particles). The population of Candidate Solutions (i.e., Particles). What is Search Space in PSO? It is the range in which the algorithm computes th...
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how is the LBP |Local Binary Pattern| values calculated? Step-by-Step with Example

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

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