Prof. Li-Yan Yuan CMPUT 391: Database Management Systems Solutions to Assignment 1 Due: 18:00‚ Feb. 10‚ 2014‚ at the 391 Drop Box 1. Present a real-life example (Not using ABCD‚ etc) to show differences between BCNF and 4NF. Solution: Consider the following table real_estate(realtor_id‚listing_property‚customer_name) used to store the information for a real estate company with one MVD constraint → realtor id → listing property | customer name. It is not difficult to see that real estate
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Using Matlab to Execute a Genetic Algorithm Optimization of Two Variable Function The function to be optimized is given by: [pic] The maximum value of this two variable function is desired‚ however Matlab’s gatool finds the minimum of fitness functions and so as in the previous example the function must be altered as follows: [pic] Now we must enter this function‚ as before‚ into a Matlab function file. Start Matlab and change the working directory to your Knowledge
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INDIAn INSTITUTE OF managEMENt KOZHIKODE | Vector Evaluated Genetic Algorithm | | Abhishek Rehan(16/301)Ankit Garg(16/308)Sanchit Garg(16/339)Sidharth Jain(16/347)12/28/2012 | ABSTRACT Many real world problems involve two types of problem difficulty: i) multiple‚ conflicting objectives and ii) a highly complex search space.On the one hand‚ instead of a single optimal solution competing goals give rise to a set of compromise solutions‚ generally denoted as Pareto-optimal. In the absence
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road length and permitted travel direction‚ waste collecting points and waste volume for each point‚ was first constructed. The proposed routing procedure comprises two main modules: grouping and routing. An OR method‚ namely Minimum Spanning Tree Algorithm‚ is modified for the calculation in the first module‚ while a GIS
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233-243. Boctor F. F.‚ 2010‚ Offsetting inventory replenishment cycles to minimize storage space‚ European Journal of Operational Research‚ 203‚ 321-325. Deb K.‚ A. Pratap‚ S. Agarwal and T. Meyarivan‚ 2002‚ A fast and elitist multi-objective Genetic algorithm: NSGA-II‚ IEEE Transactions on evolutionary computation‚ 6‚ Gallego G.‚ D. Shaw‚ and D. Simchi-Levi‚ 1992.The complexity of the staggering problem and other classical inventory problems‚ Operations Research Letters 12‚ Gallego G.‚ M. Queyranne‚ and
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programmers who wish to apply AI search techniques to complex continuous dynamical systems. In particular‚ the game programmer must “discretize” the problem‚ that is‚ approximate the continuous problem as a discrete problem suitable for an AI search algorithm. As a concrete example‚ consider the problem of navigating a simulated submarine through a set of static obstacles. This continuous problem has infinite possible states (e.g. submarine position and velocity) and infinite possible trajectories. The
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6 3.1 Runtime energy consumption calculation model 6 3.2 Energy-Aware Scheduling Algorithm 7 3.2.1 Energy Aware Scheduling by Minimizing Duplication algorithm 8 3.2.2 Experimental results and analysis 9 3.3 Dynamic provisioning and Load dispatching 9 3.3.1 Energy aware server provisioning 10 3.3.2 Forecast-based provisioning 10 3.3.2.1 Short-term load forecasting 10 3.3.3 Load Dispatching Algorithm 12 3.3.3.1 Load balancing 12 3.3.4 Evaluation of forecast provisioning and load
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Clapano Earl Karlo Mationg Contents ● Prerequisites ● Description ● Algorithm ● Example ● Analysis ● Applications ● References Iterative Deepening A-star (IDA*) CSC 171 – Introduction to AI 1 Prerequisites ● Iterative Deepening Depth-First Search ● A* algorithm Iterative Deepening A-star (IDA*) CSC 171 – Introduction to AI 2 Description Iterative Deepening A* is a graph traversal and path search algorithm that can find the shortest path between a designated start node and any
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A Genetic algorithm based crypt-steganography technique for message hiding in JPEG images Aleem Ali*‚ Sherin Zafarb‚ Reshmi Philip a) M.Tech Scholar‚ Jamia Hamdard(Hamdard University)‚ Hamdard Nager‚ N.D-110062 b) F/O Engg‚ University Polytechnic‚ JMI‚ New Delhi-110025 Email: aleem08software@gmail.com‚ sherin_zafar84@yahoo.com‚ reshmiphilip@gmail.com Running Head: A Genetic algorithm based crypt-steganography technique for message hiding in JPEG images *To whom correspondence
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are usually in the form of equations and inequalities. 2. Simplex method- is an algorithm for solving linear programming with any number of variables. Most real-world linear programming problems have more than two variables and thus are too complex for graphical solution. A procedure called the simplex method may be used to find the optimal solution to such problems. The simplex method is actually an algorithm (or a set of instructions) with which we examine corner points in a methodical fashion
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