Recent Studies in Mathematics and Computer Science Vol. 2
Synopsis
This book covers all areas of mathematics and computer science. The contributions by the authors include Hilberttype integral inequality; weight function; equivalent statement; beta function; cloud computing; load balancing; optimal solution; artificial intelligence and machine learning techniques; instancebased learning; reinforcement learning; Datanode; Hadoop; weak cluster; equilibrium point; trajectories; Normal distribution; logistic distribution; exponential distribution; best linear unbiased estimation; Riccati equation; duffing equation; integrodifferential equations; chaotic solution; differential transforms method; RungeKutta 4 (RK4) method; modified equations of Emden type; differential transforms method; RungeKutta 4 (RK4) method; FsSet; FsSubset; (FsPoint; FsBtoplogical space and FsBHausdorff 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.
Chapters

Chapter 1Equivalent Property of a HilbertType Integral Inequality Related to the Beta Function in the Whole Plane

Chapter 2Secure Information Sharing System

Chapter 3Current Research on Significance of Artificial Intelligence and Machine Learning Techniques in Smart Cloud Computing: A Review

Chapter 4CSFC: A New Centroid Based Clustering Method to Improve the Efficiency of Storing and Accessing Small Files in Hadoop: Recent Advancement

Chapter 5Research on Tanimoto Coefficient Similarity Based Mean Shift Gentle Adaptive Boosted Clustering for Genomic Predictive Pattern Analytics

Chapter 6Mathematical Modeling on a Typical Three Species Ecology

Chapter 7Record Values in the Estimation of a Parameter of Some Distributions with Known Coecient of Variation

Chapter 8The Differential Transform Method (DTM): Solution of Differential Equations

Chapter 9Solution of Modified Equations of Emdentype by Differential Transform Method: New Perspectives

Chapter 10A Discussion of Hausdorff Property on FsCartesian Product Topological Spaces

Chapter 11Arrivals Analysis

Chapter 12Departures Analysis

Chapter 13An Approach of Short Term Road Traffic Flow Forecasting Using Artificial Neural Network

Chapter 14Mean of the Probability Distribution of Departures

Chapter 15Mean to the Distribution on Arrivals 1