Learn about the Confusion Matrix with Real-Life Examples. A confusion matrix is a table that shows how well an AI model makes predictions. It compares the actual results with the predicted ones and tells which are right or wrong. It includes True Positive (TP), False Positive (FP), False Negative (FN), and True Negative (TN). Video Chapters: Confusion Matrix in Artificial Intelligence 00:00 Introduction 00:12 Confusion Matrix 03:48 Metrices Derived from Confusion Matrix 04:26 Confusion Matrix Example 1 05:44 Confusion Matrix Example 2 08:10 Confusion Matrix Real-Life Uses #artificialintelligence #machinelearning #confusionmatrix #algorithm #optimization #research #happylearning #algorithms #meta #optimizationtechniques #swarmintelligence #swarm #artificialintelligence #machinelearning
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Chemical Reaction Optimization Algorithm step-by-step with example ~xRay...
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Chemical Reaction Optimization Algorithm
Chemical Reaction Optimization algorithm is a population-based metaheuristic algorithm. Chemical Reaction Optimization algorithm is inspired by Chemical reactions. Chemical Reaction Optimization algorithm is developed by Albert Y.S. Lam and Victor O.K. Li. In this algorithm, Molecular structure (sum all characteristics) is used to compute the solution. Chemical Reaction Optimization algorithm is used to solve optimization problems.
Chemistry Basic Fundamentals: Atom / Molecule / Chemical Bonding / Molecular Structure / Molecule Energy / Chemical Reations/ Elementary Reactions
Atom: According to Dalton (in 1808), an atom is the smallest part of an element that exists as the smallest entity. 3 important fundamental particles of an atom are Proton, Electron, and Neutron.
For Example Oxygen (O), Nitrogen (N), Hydrogen (H), etc.
Molecule: A molecule is composed of 2 or more atoms held together by chemical bonds. The molecule is always formed when it is more stable and has lower energy than individual atoms. The molecule is characterized by: Atom Type, Bond Length, Bond Energy, and Angle.
For Example Water (H2O), Nitrogen (N2), Ozone (O3), Carbon Dioxide (CO2).
Energy: Capacity to do any work. Different Energy Forms are:
Light Energy
Heat Energy
Electrical Energy
Mechanical Energy
Energy Principals:
1.) Potential Energy: Potential Energy Means energy due to Object Position/condition/composition.
2.) Kinetic Energy: Kinetic Energy means capacity for doing work directly (easily transferred between objects). For Example Body in Motion.
A chemical bond is the force of attraction that holds the atoms together in a molecule.
In any chemical reaction, molecules collide with each other or with the wall of the container.
Four Elementary reactions in Chemical Reaction Optimization algorithm:
Uni-molecular Reactions
On-Wall Ineffective Collision: Collision occurred when any molecule hits the wall of the container and bounce back
Decomposition: When any molecule hit the wall it decomposes into 2 molecules
Multi molecular Reactions
Inner molecular Ineffective Collision: Two molecules collide with each other and bounce away.
Synthesis: Two molecules collide together and fuse into one molecule.
Chemical Reaction Optimization Algorithm Step-by-Step
1.) Parameter Initialization Phase
Initialize all important parameters such as:
Population Size, [Molecular Structure]
Number of Variables, [Total number of characteristics of molecule]
KineticEnergyLoassRate,[% of an upper limit of K.E. loss in the environment (in the collision)]
Molecule Collision Fraction,
Initial Kinetic Energy,
2.) Initialize population Randomly in the search space.
Population = Set of Molecules
[1,2,3,4,5,6,…..Population Size]
3.) For each molecule do
Assign a Random Solution to the molecular structure.
Calculate the Potential Energy (P.E.) using the Objective function.
Assign Kinetic Energy as Initial Kinetic Energy.
End For
4.) Further Process in Flow Chart: Chemical Reaction Optimization Algorithm Flow Chart.
Chemical Reaction Optimization algorithm Advantage:
Chemical Reaction Optimization algorithms achieve the best solutions to solve different real-world problems.
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