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Surface point location by walking algorithm for haptic visualization of triangulated 3D models

ADVANCES IN ENGINEERING SOFTWARE 2014年 75卷 58-67页

作者： Soukal, Roman Purchart, Vaclav Kolingerova, Ivana Univ W Bohemia Fac Sci Appl Dept Comp Sci & Engn Plzen 30614 Czech Republic

Haptic devices are nowadays gaining popularity because of their increasing availability. These special input/output devices provide, unlike mouse or keyboard, a native 3D manipulation, especially a more precise control and a force interaction. With more accurate description of the model, haptics can achieve more realistic force feedback. Therefore, triangulated surface models are often used for an authentic interpretation of 3D models. A common task in haptic visualization using triangulated surface models is to find a triangle which is in the collision trajectory of the haptic probe. Since the render rate of the haptic visualization is relatively high (usually about 1 kHz), the task becomes highly non-trivial for complex mesh models, especially for the meshes which are changing over time. The paper presents a fast and novel location algorithm able to find the triangle which is close to the haptic probe and in the direction of the probe motion vector. The algorithm has negligible additional memory requirements, since it does not need additional searching data structures and uses only the information usually available for triangulated models. Therefore, the algorithm could handle even triangular meshes changing over time. Results show that the proposed algorithm is fast enough to be used in haptic visualization of complex-shaped models with hundreds of thousands of triangles. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Triangle lookup searching algorithm Walking algorithm Triangulated surface model Haptic visualization Collision detection

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Reliability Assessment with Fuzzy Random Variables Using Interval Monte Carlo Simulation

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COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING 2014年第3期29卷 208-220页

作者： Jahani, Ehsan Muhanna, Rafi L. Shayanfar, Mohsen A. Barkhordari, Mohammad A. Univ Mazandaran Fac Engn & Technol Babol Sar Mazandaran Iran Georgia Inst Technol Sch Civil & Environm Engn Atlanta GA 30332 USA Iran Univ Sci & Technol Ctr Excellence Fundamental Studies Struct Engn Tehran Iran

In this work structural reliability assessment is presented for structures with uncertain loads and material properties. Uncertain variables are modeled as fuzzy random variables and Interval Monte Carlo Simulation along with interval finite element method is used to evaluate failure probability. Interval Monte Carlo is compared with existing search algorithms used in the reliability assessment of fuzzy random structural systems for both efficiency and accuracy. The genetic algorithm as one of the well developed approaches is selected for comparison. Fuzzy randomness is used as a model for handling both aleatory and epistemic uncertainties. Fuzzy quantities are calculated using the -cut approach. In the case of Interval Monte Carlo, bounds on response quantities are obtained for each -cut using only one run of interval finite element method, however genetic approach requires performing Monte Carlo Simulation for each of the considered different possible combinations within the search domain (-cut) and running finite element for each of the Monte Carlo realizations. In the presented examples both load and material uncertainties are considered. Numerical results show the computational efficiency of the Interval Monte Carlo approach and its superiority to the alternative search approaches such as optimization and genetic algorithms. In addition, results show how that Interval Monte Carlo approach provides guaranteed and sharp enclosure to the system solution.

关键词： Genetic algorithm (GA) Fuzzy Random variable Monte Carlo technique Hypoderma Finite element method searching algorithm reliability evaluation

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Multiobjective optimization method based on adaptive parameter harmony search algorithm

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Journal of Applied Mathematics 2015年第Pt.1期2015卷 165601-1-165601-12页

作者： Sabarinath, P. Thansekhar, M.R. Saravanan, R. K.L.N College of Engineering Pottapalayam 630611 India Sri Krishna College of Technology Coimbatore 641 042 India

The present trend in industries is to improve the techniques currently used in design and manufacture of products in order to meet the challenges of the competitive market. The crucial task nowadays is to find the optimal design and machining parameters so as to minimize the production costs. Design optimization involves more numbers of design variables with multiple and conflicting objectives, subjected to complex nonlinear constraints. The complexity of optimal design of machine elements creates the requirement for increasingly effective algorithms. Solving a nonlinear multiobjective optimization problem requires significant computing effort. From the literature it is evident that metaheuristic algorithms are performing better in dealing with multiobjective optimization. In this paper, we extend the recently developed parameter adaptive harmony search algorithm to solve multiobjective design optimization problems using the weighted sum approach. To determine the best weightage set for this analysis, a performance index based on least average error is used to determine the index of each weightage set. The proposed approach is applied to solve a biobjective design optimization of disc brake problem and a newly formulated biobjective design optimization of helical spring problem. The results reveal that the proposed approach is performing better than other algorithms. © 2015 P. Sabarinath et al.

关键词： Multiobjective Optimization Method Adaptive Self tuning searching algorithm optimization method MECHANICAL COMPONENTS Optimal design design variable

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Distributed Heuristic Forward Search for Multi-agent Planning

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JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH 2014年第1期51卷 293-332页

作者： Nissim, Raz Brafman, Ronen Ben Gurion Univ Negev IL-84105 Beer Sheva Israel

This paper deals with the problem of classical planning for multiple cooperative agents who have private information about their local state and capabilities they do not want to reveal. Two main approaches have recently been proposed to solve this type of problem - one is based on reduction to distributed constraint satisfaction, and the other on partial-order planning techniques. In classical single-agent planning, constraint-based and partial-order planning techniques are currently dominated by heuristic forward search. The question arises whether it is possible to formulate a distributed heuristic forward search algorithm for privacy-preserving classical multi-agent planning. Our work provides a positive answer to this question in the form of a general approach to distributed state-space search in which each agent performs only the part of the state expansion relevant to it. The resulting algorithms are simple and efficient - outperforming previous algorithms by orders of magnitude - while offering similar flexibility to that of forward-search algorithms for single-agent planning. Furthermore, one particular variant of our general approach yields a distributed version of the A* algorithm that is the first cost-optimal distributed algorithm for privacy-preserving planning.

关键词： constraint satisfaction problems A* algorithm Heuristics algorithms Forward search searching algorithm Planning Techniques Distribute

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Optimal motion for obstacle stepping in a hybrid wheeled-legged hexapod

Optimal motion for obstacle stepping in a hybrid wheeled-leg...

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IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Gomez-Bravo, Fernando Aznar, Mariano J. Carbone, Giusseppe Univ Huelva Elect Syst & Mechatron Grp Palos De La Frontera Huelva Spain Univ Cassino & So Lazio Cassino Lab Robot & Mech Cassino Italy

ISBN: (纸本)9781479942541

This paper presents a methodology for obtaining optimal motions for the leg of a hybrid wheeled-legged hexapod. The aim of the approach is to compare motion strategies for a leg when it has to step over an obstacle. The study is numerically solved by referring to a prototype of a hexapod built at LARM in the Cassino University. The motion planning procedure is a combination of a quick random search algorithm (Rapidly Exploring Random Trees) together with an optimisation method (Genetic algorithm).

关键词： Hexapoda Leg searching algorithm stepping digitally HYBRID Hybrid electric vehicles

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Modeling Large Distribution Feeders for Transient Analysis using Graph Search algorithms

Modeling Large Distribution Feeders for Transient Analysis u...

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North American Power Symposium (NAPS)

作者： Nagarajan, Adarsh Ayyanar, Raja Arizona State Univ Dept Elect Engn Tempe AZ 85287 USA

ISBN: (纸本)9781479959044

This paper proposes a network modeling technique using a graph search algorithm for model development of large distribution feeders in an electromagnetic transient program. Large scale penetration of distributed energy resources in the existing distribution feeders impacts the dynamic behavior and pose the motivation to perform a transient analysis on the distribution feeders. This paper proposes a generalized framework to develop the feeder model suitable for transient analysis. A complete model of the distribution feeder will be developed with the purpose to capture the long-term transients such as interaction with other control devices, cloud transients, and voltage flicker. For this purpose a test distribution system is chosen with 738 nodes, 1142 sections, 174 transformers, 107 PV generators, and 287 spot loads. The test feeder has been modeled in MATLAB/Simulink for performing the transient analysis.

关键词： EMTP distributed power generation distribution networks graph theory search problems MATLAB Simulink cloud transients control devices distributed energy resources electromagnetic transient program graph search algorithms large distribution feeders large distribution feeders modeling model development transient analysis voltage flicker algorithm design and analysis Analytical models Generators Load modeling Mathematical model Software packages Transient analysis Transient analysis Electromagnetic Transients Program Voltage flicker searching algorithm distributed energy resources distribution feeder Control apparatus algorithm design and analysis model design distributed power generation tabu search Software packages Load modeling dynamos Power grids

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Optimizing Pump Operation Scheduling for Water Supply Systems

Optimizing Pump Operation Scheduling for Water Supply System...

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IEEE International Conference on System Science and Engineering (ICSSE)

作者： Ueno, Yohei Mori, Kazuyuki Mitsubishi Electr Corp Amagasaki Hyogo 661 Japan

ISBN: (纸本)9781479943678

We develop a new method to plan pump operation schedules for water supply systems. In the method, we define a solution space as a network model in which the nodes are cumulative flow rates and the edges are the flow rates at each time step. We treat pump scheduling as a shortest path problem, and the A(star) search algorithm is used to find the optimum path. One feature of the proposed method is that the search area is restricted by constraints, such as the water level of tanks. We examine this scheduling method by attempting to solve a benchmark problem and evaluated the accuracy and the computing time. The experimental results show that the method can make suitable solutions within an acceptable waiting time. We confirmed that the proposed method can be used effectively for large-scale water supply systems.

关键词： Optimization Reservoirs Water supply systems reservoirs pump operation Flow rates Benchmark testing searching algorithm Solution space Water levels network model Shortest path problem Dams Reservoir waters

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Improving Portfolio Risk Profile with Threshold Accepting

Improving Portfolio Risk Profile with Threshold Accepting

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IEEE Conference on Computational Intelligence for Financial Engineering and Economics (CIFEr)

作者： Kleinknecht, Manuel Ng, Wing Lon Univ Essex Ctr Computat Finance & Econ Agents Colchester CO4 3SQ Essex England

ISBN: (纸本)9781479923809

The application of the Threshold Accepting (TA) algorithm in portfolio optimisation can reduce portfolio risk compared with a Trust-Region local search algorithm. In a benchmark comparison of several different objective functions combined with different optimisation routines, we show that the TA search algorithm applied to a Conditional Value at Risk (CVaR) objective function yields the lowest Basel III market risk capital requirements. Not only does the TA algorithm outmatch the Trust-Region algorithm in all risk and performance measures, but when combined with a CVaR or 1% VaR objective function, it also achieves the best portfolio risk profile.

关键词： Heuristicalgorithms Investment Linearprogramming Optimization Portfolios Reactivepower Standards Investments Objective function BRIEFCASE searching algorithm TEST AUTHORIZATIONS TA tantalum

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Constrained control of non-playing characters using Monte Carlo Tree Search

Constrained control of non-playing characters using Monte Ca...

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IEEE Conference on Computational Intelligence and Games (CIG)

作者： Sanselone, Maxime Sanchez, Stephane Sanza, Cedric Panzoli, David Duthen, Yves Univ Toulouse IRIT CNRS UMR 5505 F-31042 Toulouse France

ISBN: (纸本)9781479935475

In this paper, we apply the Monte Carlo Tree Search (MCTS) method for controlling at once several virtual characters in a 3D multi-player learning game. The MCTS is used as a search algorithm to explore a search space where every potential solution reflects a specific state of the game environment. Functions representing the interaction abilities of each character are provided to the algorithm to leap from one state to another. We show that the MCTS algorithm successfully manages to plan the actions for several virtual characters in a synchronized fashion, from the initial state to one or more desirable end states. Besides, we demonstrate the ability of this algorithm to fulfill a specific requirement of a learning game AI : guiding the non player characters to follow a predefined and constrained learning scenario and, if necessary, to adapt their decision to unexpected events in the simulation.

关键词： Backpropagation Bismuth Diagnostic radiography Instruments Surgery diagnostic radiography back propagation bismuth Tree searching Surgery Character searching algorithm Hunting Game theory Game animals Hypoderma

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Energy Optimization of a High Consistency Refiner Process

Energy Optimization of a High Consistency Refiner Process

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IEEE Conference on Control Applications (CCA)

作者： Hohn, Patrick Birk, Wolfgang Lulea Univ Technol Dept Comp Sci Elect & Space Engn Control Engn Grp SE-97187 Lulea Sweden

ISBN: (纸本)9781479974092

This paper presents a concept for energy optimization dealing with high consistency (HC) refining processes in the pulp and paper industry. Models for the outlet consistency and Gurley number used in the optimization are briefly described. The specific energy is used as manipulated variable. Additionally, the inlet consistency can be adjusted to a fixed value. While keeping the energy consumption as low as possible, it is still attempted to keep outlet consistency and Gurley number close to its desired value. The optimization uses a cost function with quadratic terms. An explicit solution for the optimization problem is derived. Additionally, the results are compared with findings from numerical optimization using a global search algorithm and an interior point method. Results presented are consistent with each other and indicate potential for energy savings.

关键词： Cost function Energy consumption Entropy Equations Mathematical model Numerical models Cost functions energy consumption numerical models Mathematical Model entropy energy saving searching algorithm Paper and pulp industry consistency Consistency (Measurement) Refiners Explicit Solution specific energy

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