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International Conference on Cyberspace Technology (CCT 2014)

作者： Sun Dandan Zhang Hongxin School of Electronic Engineering Beijing University of Posts and Telecommunications 100876 China Sch. of Electron. Eng. Beijing Univ. of Posts & Telecommun. Beijing China

ISBN: (纸本)9781510802704

Cooperative routing selection algorithm is based on the limited bandwidth and collaborative remain energy, according to pheromone concentration in Ant colony optimization algorithm. The ant colony optimization algorithm is applied to improving collaboration network routing problems to reduce network congestion and reduce node energy consumption. Simulation demonstrate that the algorithm obtains a global optimization and makes an average 60% reduction in end to end delay, increased the utilization of network resources.

关键词： Ant colony optimization algorithm Pheromone density The Cooperative routing ant algorithm Ant colony optimization Network routing Web resources optimization algorithms Network Congestion selection algorithm Global optimization algorithms selection methods node energy

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Hybrid Inference optimization for Robust Pose Graph Estimation

Hybrid Inference Optimization for Robust Pose Graph Estimati...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Aleksandr V. Segal Ian D. Reid University of Oxford University of Adelaide

ISBN: (纸本)9781479969357

In this paper we introduce a new optimization algorithm for networks of switched nonlinear objectives and apply this to the important problem of pose graph estimation for robot localization and mapping. The key insight is to replace the linear solver typically used in Gauss-Newton style methods with hybrid inference over switched discrete/continuous linear Gaussian networks. Since exact inference in these networks is known to be NP-hard, we also propose an approximate inference algorithm for the linearized hybrid networks based on message passing. We apply the new algorithm to the problem of robust pose graph estimation in the presence of incorrect loop closures and compare against three recently published approaches to the same problem. Evaluation is performed on ten sequences from two different datasets and shows that our approach performs substantially better than the state of the art.

关键词： optimization algorithms state of the art hybrid network Inference algorithms Robustness Network Nondeterministic polynomial-time hard

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Biometric System for Measuring Gait and Fall Characteristics Captured on Video

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JOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME 2014年第7期136卷 071005-071005页

作者： Firmani, Flavio Robinovitch, Stephen N. Park, Edward J. Univ Victoria Dept Mech Engn Victoria BC V8W 3P6 Canada Simon Fraser Univ Dept Biomed Physiol & Kinesiol Burnaby BC V5A 1S6 Canada Simon Fraser Univ Sch Mechatron Syst Engn Surrey BC V3T 0A3 Canada

This paper presents a methodology that quantifies gait and fall characteristics from video of real-life fall events. The method consists in selecting on-screen the points on the ground where the feet are in contact with the ground. The essence of the method lies in establishing a transformation from the video frames to the "real world." In projected images, geometric properties such as lengths, angles, and parallelism are not preserved;thus, concepts of projective geometry are applied, namely homography. Because the ground is an invariant plane, using this plane for homography results in a constant transformation. The homographic transformation relies on the accuracy in the selection of on-screen points. An optimization algorithm that minimizes the errors caused by inaccurate on-screen point selection improves the results of the homographic transformation. Experimental trials are conducted at three walking velocities (slow, preferred, and fast) using two video cameras and a GAITRite walkway system. Spatial parameters of two independent video analyses are compared with the GAITRite system, yielding a limit of agreement of step length from -2.12 cm to 2.03 cm. Temporal parameters are less confident due to the existence of dropped frames in the video footage. This method is then used to analyze two real fall events as demonstrative cases. First, the gait characteristics are analyzed before imbalance, and subsequently, the characteristics of stepping are analyzed during the fall. In particular, we propose the stepping/impact angle as the metric that quantifies how much stepping affected the direction of the fall.

关键词： Calibration Errors Gait analysis Geometry Biometry Video cameras optimization algorithms Door frames

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An efficient technique to solve combined economic and emission dispatch problem using modified Ant colony optimization

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SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES 2013年第4期38卷 545-556页

作者： Gopalakrishnan, R. Krishnan, A. KS Rangasamy Coll Technol Dept Elect & Elect Engn Tiruchengode 637215 India

Economic load dispatch is one of the vital purposes in electrical power system operation, management and planning. Economic dispatch problem is one of the most important problems in electric power system operation. In large scale system, the problem is more complex and difficult to find out optimal solution because it is nonlinear function and it contains number of local optimal. Combined economic emission dispatch (CEED) problem is to schedule the committed generating units outputs to meet the required load demand at minimum operating cost with minimum emission simultaneously. The main aim of economic load dispatch is to reduce the total production cost of the generating system and at the same time the necessary equality and inequality constraints should also be fulfilled. This leads to the development of CEED techniques. There are various techniques proposed by several researchers to solve CEED problem based on optimization techniques. But still some problems such as slower convergence and higher computational complexity exist in using the optimization techniques such as GA for solving CEED problem. This paper proposes an efficient and reliable technique for combined fuel cost economic optimization and emission dispatch using the Modified Ant Colony optimization algorithm (MACO) to produce better optimal solution. The simulation results reveal the significant performance of the proposed MACO approach.

关键词： Combined economic emission dispatch (CEED) optimization algorithms power demand Ant colony optimization modified Ant colony optimization (MACO)

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Integrating Design for Assembly Guidelines in Packaging Design with a Context-based Approach

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Procedia CIRP 2014年 21卷 342-347页

作者： P. Betancur-Muñoz G. Osorio-Gómez J.F. Martínez-Cadavid J.F. Duque-Lombana Design Engineering Research Group Universidad EAFIT Medellín Colombia Applied Mechanics Research Group Universidad EAFIT Medellín Colombia

In the product lifecycle, the packaging, as an object, has been on the back burner with respect to product and production systems design and some authors stated that its influence starts at the packing stage and ends when the customer obtains the product. Only a few years ago, its strategic role, protecting, containing and preserving the product, has been recognized, both in theory and in practice [1]. In this way, the packaging design has been focused in the accomplishment of some specific objectives, such as cost and space saving, material reduction, and quality problems avoidance. These approaches are object-related, but the design process is not considering that the packaging is also utilized to handle, transport, distribute, retail and promote the product. Therefore, even if mathematical solutions could be obtained for space optimization problems, these could not be relevant at industrial level since they are unfeasible throughout the packaging lifecycle, from either logistics or quality standpoints; and new restrictions should be considered. An approach proposed by Lee & Lye [2], called “Design for manual Packaging (DFPkg)”, is based on Design for the Environment (DFEnv) and Design for Assembly (DFA) guidelines, since the activities related with packaging could be considered as assembly activities seeing that all the packed pieces are part of a unique system. Nevertheless, some guidelines from DFA are omitted or decontextualized and they are not connected to restrictions in the mathematical models. This paper presents an integral approach for packaging design, complementing the guidelines proposed by Lee & Lye [2] in key contexts of the packaging lifecycle, in order to generate restrictions for an optimization model. Besides, this approach has been validated with a real industrial case study where the obtained solution is compared with the current one.

关键词： Packaging Design Design for Assembly optimization algorithms

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A new quadratic programming strategy for efficient sparsity exploitation in SQP-based nonlinear MPC and MHE

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IFAC Proceedings Volumes 2014年第3期47卷 2945-2950页

作者： Janick V. Frasch Milan Vukov Hans Joachim Ferreau Moritz Diehl Department of Electrical Engineering KU Leuven Belgium Department of Mathematics Magdeburg University Germany ABB Corporate Research Baden-Dättwil Switzerland

A large class of algorithms for nonlinear model predictive control (MPC) and moving horizon estimation (MHE) is based on sequential quadratic programming and thus requires the solution of a sparse structured quadratic program (QP) at each sampling time. We propose a novel algorithm based on a dual two-level approach involving a nonsmooth version of Newton's method that aims at combining sparsity exploitation features of an interior point method with warm-starting capabilities of an active-set method. We address algorithmic details and present the open-source implementation qpDUNES. The effectiveness of the solver in combination with the ACADO Code Generation tool for nonlinear MPC is demonstrated based on set of benchmark problems, showing significant performance increases compared to the established condensing-based approach, particularly for problems with long prediction horizons.

关键词： Predictive Control optimization algorithms Open-Source Software

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A novel artificial bee colony algorithm for HVAC optimization problems

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HVAC&R RESEARCH 2013年第6期19卷 715-731页

作者： Zhang, Xin Fong, Kwong Fai Yuen, Shiu Yin City Univ Hong Kong Dept Elect Engn Kowloon Hong Kong Peoples R China City Univ Hong Kong Div Bldg Sci & Technol Kowloon Hong Kong Peoples R China

The strategy of simulation-optimization is popular in handling the design and energy management of centralized HVAC systems. An effective optimization algorithm is paramount to obtain the optimal design and operation of HVAC systems. Due to the multi-dimensional and highly constrained nature commonly found in HVAC problems, traditional optimization methods are generally not applicable. Instead, a metaheuristc algorithm, e.g., the genetic algorithm, is a good choice to achieve these purposes. In recent years, the paradigm of the artificial bee colony is emerging in the field of evolutionary computation. The artificial bee colony optimizes the problem through the foraging behavior of honey bees. This article presents a novel approach developed from this paradigm, called the one-position inheritance artificial bee colony algorithm, for handling HVAC system optimization. Through two HVAC example problems, it is found that the one-position inheritance artificial bee colony can more effectively and efficiently search the optimal solutions against the genetic algorithm and original artificial bee colony. This suggests that the one-position inheritance artificial bee colony is a good optimization algorithm to solve other HVAC engineering problems with a multi-dimensional, mixed discrete-continuous, and highly constrained search landscape.

关键词： bee colonies High Voltage Alternating Current Systems artificial bee colony algorithm heating ventilation and air conditioning optimization algorithms Bee Dosage Form Not Applicable Genetic Algorithm (GA) Inheritance

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Adaptive Distributed MIMO Radar Waveform optimization Based on Mutual Information

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2013年第2期49卷 1374-1385页

作者： Chen, Yifan Nijsure, Yogesh Yuen, Chau Chew, Yong Huat Ding, Zhiguo Boussakta, Said South Univ Sci & Technol China Dept Elect & Comp Engn Shenzhen 518055 Guangdong Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Singapore Univ Technol & Design Singapore 138682 Singapore Inst Infocomm Res Singapore 138632 Singapore Newcastle Univ Sch Elect & Elect Engn Newcastle Upon Tyne NE1 7RU Tyne & Wear England

A novel approach to optimizing the waveforms of an adaptive distributed multiple-input multiple-output (MIMO) radar is developed. The research work aims at improving the target detection and feature extraction performance by maximizing the mutual information (MI) between the target impulse response and the received echoes in the first step, and then minimizing the MI between successive backscatter signals in the second step. These two stages correspond to the design of the ensemble of excitations and the selection of a suitable signal out of the ensemble, respectively. The waveform optimization algorithm is based upon adaptive learning from the radar scene, which is achieved through a feedback loop from the receiver to the transmitter. This feedback includes vital information about the target features derived from the reflected pulses. In this way the transmitter adjusts its probing signals to suit the dynamically changing environment. Simulation results demonstrate better target response extraction using the proposed two-step algorithm as compared with each single-step optimization method. This approach also results in improved target detection probability and delay-Doppler resolution as the number of iterations increases.

关键词： Feedback loop IMPULSE RESPONSE Object detection Feature extraction iterative methods waveforms Transmitter Excitation MIMO radar signals optimization algorithms Research work optimization method ENVIRONMENT SIMULATION Self tuning

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Film Cooling optimization Using Numerical Computation of the Compressible Viscous Flow Equations and Simplex Algorithm

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INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING 2013年第1期2013卷 11.1-11.24页

作者： Elsayed, Ahmed M. Owis, Farouk M. Rahman, M. Madbouli Abdel Inst Aviat Engn & Technol Giza Egypt Cairo Univ Fac Engn Dept Aerosp Engn Giza 12211 Egypt

Film cooling is vital to gas turbine blades to protect them from high temperatures and hence high thermal stresses. In the current work, optimization of film cooling parameters on a flat plate is investigated numerically. The effect of film cooling parameters such as inlet velocity direction, lateral and forward diffusion angles, blowing ratio, and streamwise angle on the cooling effectiveness is studied, and optimum cooling parameters are selected. The numerical simulation of the coolant flow through flat plate hole system is carried out using the "CFDRC package" coupled with the optimization algorithm "simplex" to maximize overall film cooling effectiveness. Unstructured finite volume technique is used to solve the steady, three-dimensional and compressible Navier-Stokes equations. The results are compared with the published numerical and experimental data of a cylindrically round-simple hole, and the results show good agreement. In addition, the results indicate that the average overall film cooling effectiveness is enhanced by decreasing the streamwise angle for high blowing ratio and by increasing the lateral and forward diffusion angles. Optimum geometry of the cooling hole on a flat plate is determined. In addition, numerical simulations of film cooling on actual turbine blade are performed using the flat plate optimal hole geometry.

关键词： Cooling effects Cooling hole Angle compressible numerical simulation air blowing ratio numerical calculation optimization algorithms Film cooling Flat slabs TURBINE BLADE Simplex Film cooling effectiveness

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optimization of thickness uniformity of optical coatings on a conical substrate in a planetary rotation system

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APPLIED OPTICS 2013年第4期52卷 B26-B32页

作者： Guo, Chun Kong, Mingdong Liu, Cunding Li, Bincheng Chinese Acad Sci Inst Opt & Elect Chengdu 610209 Peoples R China Univ Chinese Acad Sci Beijing 100039 Peoples R China

For a coating machine with a planetary rotation system and counterrotating shadowing mask configuration, a shadowing mask was designed using a numerical optimization algorithm to control the thickness uniformity of optical coatings formed on conical substrate. Single-layer magnesium fluoride (MgF2) and antireflective (AR) coating at 193 nm were fabricated on a convex conical substrate holder (with diameter 225 mm, apex angle 140 deg, and height 41 mm) by thermal evaporation. Thickness distribution determined from the transmittance spectra of single-layer MgF2 thin films on BK7 slices showed that uniformities better than 99.3% were experimentally achieved with the designed counterrotating shadowing mask. From the reflectance spectra, uniform optical performance was also obtained for the 193 nm AR coating deposited on fused-silica substrates. (C) 2013 Optical Society of America

关键词： Conical Antireflection coatings TRANSMISSION SPECTROSCOPY Reflection spectra Optical coatings Uniformity COUNTERROTATION optimization algorithms Substrates COATERS Shadowing (Histology) PLANETARY ROTATION

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