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In pseudocode the algorithm can be stated as: Begin 1) Objective function: (), = (,,...,); 2) Generate an initial population of fireflies (=,, …,);. 3) Formulate light intensity I so that it is associated with () (for example, for maximization problems, () or simply = ();) 4) Define absorption coefficient γ while (t < MaxGeneration) for i = 1 : n (all n fireflies) for j = 1 : i (n fireflies ...
A Gaussian minus exponential distribution has been suggested for modelling option prices. [20] If such a random variable Y has parameters μ , σ , λ , then its negative -Y has an exponentially modified Gaussian distribution with parameters -μ , σ , λ , and thus Y has mean μ − 1 λ {\displaystyle \mu -{\tfrac {1}{\lambda }}} and variance ...
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...
In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate; the distance parameter could be any meaningful mono-dimensional measure of the process, such as time ...
The matrix exponential satisfies the following properties. [2] We begin with the properties that are immediate consequences of the definition as a power series: e 0 = I; exp(X T) = (exp X) T, where X T denotes the transpose of X. exp(X ∗) = (exp X) ∗, where X ∗ denotes the conjugate transpose of X. If Y is invertible then e YXY −1 = Ye ...
The softmax function, also known as softargmax [1]: 184 or normalized exponential function, [2]: 198 converts a vector of K real numbers into a probability distribution of K possible outcomes. It is a generalization of the logistic function to multiple dimensions, and is used in multinomial logistic regression .
SymPy is an open-source Python library for symbolic computation.It provides computer algebra capabilities either as a standalone application, as a library to other applications, or live on the web as SymPy Live [2] or SymPy Gamma. [3]
The standard logistic function is the logistic function with parameters =, =, =, which yields = + = + = / / + /.In practice, due to the nature of the exponential function, it is often sufficient to compute the standard logistic function for over a small range of real numbers, such as a range contained in [−6, +6], as it quickly converges very close to its saturation values of 0 and 1.