Particle Swarm Optimization - Demystified

IntroductionParticle Swarm Optimization(PSO) is a swarm intelligence based meta-heuristic, used for finding optimal solutions in large search-spaces; such as the infamous Genetic Algorithm. PSO outperforms most optimization algorithms in terms of speed and convergence in the continuous-space domain...

Read More

The Genetic Algorithm - Explained

Paradigm of Evolution Every organism contains an array of traits - called DNA, when 2 parents mate they produce a child containing a mixture of their DNA. Depending on how well those traits work together to help the child survive so that he may reproduce, will determine if those traits will pass into future generation. Rarely a random trait enters a child's DNA that was not inherited from the parents,...

Read More

Neural Network Illustrated – Step by Step

I1 and I2 are the inputs scaled to [-1,1] or [0, 1], depending on the activation function used f()=Activation Function=Tanh(), Sigmoid() or any differential-able function W=Current neurons input weights, initialized randomly between [-1, 1]. Wb=Bias Weight, connected to nothing, used as a threshold,...

Read More

Markov Chains - Explained

Markov Chains is a probabilistic process, that relies on the current state to predict the next state. For Markov chains to be effective the current state has to be dependent on the previous state in some way; For instance, from experience we know that if it looks cloudy outside, the next state we expect is rain. We can also say that when the rain starts to subside into cloudiness, the next state will...

Read More

Bloom Filters - Explained

The Bloom filter is a space efficient, probabilistic data structure, designed to test the membership of elements to a set. The trade-off for being a space efficient data structure is it may return false positives, but always returns definite negatives: Meaning Bloom filters can accurately test an element for non-membership to a set, but can only with probability test an element for membership. Bloom...

Read More