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    machine languages. And therefore, when I had the chance to select my major before the university, I chose Computer Science without any doubt or hesitation. During my undergraduate study at Iowa University, what I learn most are basic languages and algorithms, but some of the advanced courses and self-learning make me feel that computer science demonstrate the essence of natural science - evolution. For example, the development of website from static to dynamic, the progress of the sense…

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    International Olympiad of Informatics to represent India, there was no doubt that I wanted to build things faster and more efficient than before. However, until then I did not know the booming field called machine learning. I always tried to make algorithms to predict something based on heuristic decisions or even just hardcoded bunch of decisions. It was only in UCSD when I took my first Machine learning course, I realized the true potential of Machines and Data and the sweet bond between…

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    presently there is no polynomial solution available. In this paper we try to solve this very hard problem using various heuristics such as Simulated Annealing, Genetic Algorithm to find a near optimal solution as fast as possible. We try to escape the local optimum, using these advanced heuristic techniques. Keywords - Genetic Algorithm; Simulated Annealing; heuristic; 1. Introduction Travelling salesman problem can be formulated as “For given list of nodes determine the shortest tour…

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    as follows. First, M isolated modules, each with the WS structure, are constructed, In order to generate such networks, we used the random rewiring algorithm proposed by Watts–Strogatz[5], Considering a ring graph with n nodes each connected to its m-nearest neighbours by undirected links. The total number of the links are Q=2mn. The rewiring algorithm includes Q steps, and at each step i, link i are chosen and rewired to a node randomly chosen over the graph with the intra-modular rewiring…

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    known as the first computer programmer. Ada worked with Charles Babbage on his Analytical Engine, a proposed mechanical, general-purpose computer and the beginnings of computer programming. Her notes included the first of what is now known as an algorithm. She is the only legitimate child of the Romantic poet, Lord Byron. ==Young Life and Education== Ada Lovelace was born Augusta Ada Byron King on December 10, 1815, the only legitimate child produced by the famous poet George Lord Byron and…

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    I was contacted by my old coding teacher and received the opportunity to assist her in leading this year’s coding program. Although I knew I wasn't the best at coding, I saw this offer as a chance for me to learn more about it while sharing the little that I knew with others. During last year's program I got the opportunity to create my own games/programs/apps, and I learned more about JavaScript and its role in businesses. With this information I realized that knowing at least basic code is…

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    Describe how the quicksort works including a discussion of the pivot, how it is selected, and why the pivot is important to the quicksort. Let’s start describing what pivot is, its function and why is so important. The pivot is the element that basically divides the array in two halves, where the left half contains the smaller values and the right half contains the greater values. The pivot can be selected in many ways. First, last, middle element, actually any element of the array can be…

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    selection can be costly endeavour. This paper proposes two new feature selection algorithms, based on binary particle swarm optimisation, with the aim of reducing running time without affecting classification accuracy by combining filter and wrapper approaches. The first algorithm proceeds cautiously by only updating the pbest and gbest, two critical values, after the learning system has been consulted. The second algorithm performs more reckless updates with the aim of sacrificing some…

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    SVM And Genetic Algorithm

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    is maximized. SVM is useful for kernel trick to map the novel input space into a high dimensional feature space to improve the classifier generalization ability when the training data is not linear splitable. GA(Genetic Algorithm) is a stochastic and the empirical searching algorithm that is stimulated by natural evolution. The candidate solutions are encoded to a group of strings (called chromosomes) by some kind of encoding method in the evolution.The best candidate solution is obtained after…

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    linear programming problem forms a convex polygon in the best possible scenario. It is imperative to obtain a process that would assist in determining the optimal solution without the need to examine the graphical representation. The need for an algorithm that would perform such process was essential in the early days of the formulations of linear programming problems. Although challenging, the task was accomplished by a mathematician of the twentieth century. In 1947, George Dantzig…

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