Recent Studies in Mathematics and Computer Science Vol. 2

This book covers all areas of mathematics and computer science. The contributions by the authors include Hilbert-type integral inequality; weight function; equivalent statement; beta function; cloud computing; load balancing; optimal solution; artificial intelligence and machine learning techniques; instance-based learning; reinforcement learning; Datanode; Hadoop; weak cluster; equilibrium point; trajectories; Normal distribution; logistic distribution; exponential distribution; best linear unbiased estimation; Riccati equation; duffing equation; integro-differential equations; chaotic solution; differential transforms method; Runge-Kutta 4 (RK4) method; modified equations of Emden type; differential transforms method; Runge-Kutta 4 (RK4) method; Fs-Set; Fs-Subset; (Fs-Point; FsB-toplogical space and FsB-Hausdorff space; random variable; continuous probability distribution; artificial neural network; intelligent transport system; departure rate; density function; mean of the distribution; normalizing constant etc. This book contains various materials suitable for students, researchers and academicians in the field of mathematics and computer Science.