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检索条件"主题词=Optimization algorithms"

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DMEA-II and its application on spam email detection problems

DMEA-II and its application on spam email detection problems

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7th IEEE Symposium on Computational Intelligence for Security and Defense Applications (IEEE-CISDA)

作者： Long Nguyen Anh Quang Tran Lam Thu Bui Le Quy Don Tech Univ Fac Informat Technol Hanoi Vietnam Univ Hanoi Fac Informat Technol Hanoi Vietnam

ISBN: (纸本)9781479954315

This paper deals with multi-objectitivty in the problem of Vietnamese spam detection. We first analyze the problem taking into account the specific Vietnamese characterises as well as multi-objectivity. With the use of multi-objectivity, we can allow the users more flexibility on selecting the solution. Our proposal is to extende a multi-objective optimization algorithm using directional information, called DMEA-II for finding sets of feasible trade-off solutions for an anti-spam email system (using Apache SpamAssassin). The two objectives for considering are the Spam Detection Rate (SDR) and False Alarm Rate (FAR). The experiments were conducted based on spam data sets through several scenarios with different numbers of SpamAssassin rules. According to the obtained results, the new approach based on DMEA-II not only achieved more efficient results but also created a set of ready-to-use rule scores trading-off between SDR and FAR. It demonstrates the ability to give users more flexibility and efficiency in the Anti-spam email System.

关键词： optimisation security of data unsolicited e-mail Apache Spam Assassin DMEA-II FAR SDR Vietnamese spam detection antispam email system directional information false alarm rate multiobjective optimization algorithm spam detection rate spam email detection problems Databases Electronic mail Optical fibers optimization Sociology Statistics Training Unsolicited electronic mail FEDERAL AVIATION REGULATION SDPR gene false alarm probability electronic mail Data Security Sociology Optical Fibers optimization algorithms Database Functional training

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optimization Algorithm and Practical Implementation for 2-coil Wireless Power Transfer Systems

Optimization Algorithm and Practical Implementation for 2-co...

引用

American Control Conference

作者： Wenshan Hu Hong Zhou Qijun Deng Xingran Gao Department of Automation School of Power and Mechanical Engineering Wuhan University Wuhan 430072 China

ISBN: (纸本)9781479932757

Wireless power transfer based on inductive coupling techniques has attracted a lot of research interest in recent years. It can be potentially applied in many industrial sections. However, the harsh outdoor industrial environment could induce circuit parameter drift. Only small drift may result in huge performance drop, as the circuits are very sensitive to the parameter changes. In order to address the problem, an optimization method to compensate for the effect of drifting parameters and track the maximum performance is introduced in this paper. A switch network which is able to dynamically change the inductance of the Tx coil is designed. When the parameter drift occurs, the tuning algorithm is able to adjust both the exciting frequency and the Tx coil inductance. By measuring the input power only, the best working point can be found out without requiring any measurement on the Rx side. Therefore, the algorithm can be implemented in the controller located on the Tx side without coordination and communication between both sides. In order to verify the effectiveness of the proposed method, a test rig is setup and practical experiments are conducted. The experimental results are also presented in the paper.

关键词： optimization algorithms Inductance excitation frequency Switching networks Transmission systems Drift optimization method circuit parameter Workstations sidings

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optimization and management of energy power flow in hybrid electrical vehicles

Optimization and management of energy power flow in hybrid e...

引用

5th IET Hybrid and Electric Vehicles Conference (HEVC 2014)

作者： G. Gruosso Politecnico di Milano Milano Lombardia IT

ISBN: (纸本)9781510800021

The use of optimization algorithm for the management of energy on vehicles electrical, is an innovative argument in the field of the transports. In this context, beginning from an accurate model of electrical device, is necessary to identify the performances so as to reproduce the physical behavior of the considered vehicle. Particularly it is necessary to start from a model that takes into account several details including Battery and all the electrical loads.

关键词： Energy Management Optimisation Hybrid Electrical Vechicle Energy management Electric devices vehicle Motor Activity transport optimization algorithms Electricity Power flow Batteries Necessary organisation and administration Electric loads

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optimization OF ZERO-DELAY MAPPINGS FOR DISTRIBUTED CODING BY DETERMINISTIC ANNEALING

OPTIMIZATION OF ZERO-DELAY MAPPINGS FOR DISTRIBUTED CODING B...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Mustafa S. Mehmetoglu Emrah Akyol Kenneth Rose Department of Electrical and Computer Engineering University of California Santa Barbara CA 93106

ISBN: (纸本)9781479928941

This paper studies the optimization of zero-delay analog mappings in a network setting that involves distributed coding. The cost surface is known to be non-convex, and known greedy methods tend to get trapped in poor locally optimal solutions that depend heavily on initialization. We derive an optimization algorithm based on the principles of "deterministic annealing", a powerful global optimization framework that has been successfully employed in several disciplines, including, in our recent work, to a simple zero-delay analog communications problem. We demonstrate strict superiority over the descent based methods, as well as present example mappings whose properties lend insights on the workings of the solution and relations with digital distributed coding.

关键词： deterministic annealing MAPPING(MATHEMATICAL) distributed coding optimization algorithms greedy method annealing Non-Convex initialization disciplines

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Tight Semidefinite Relaxation for Combinatorial optimization in UWB Multiuser Detection Systems

Tight Semidefinite Relaxation for Combinatorial Optimization...

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IEEE Vehicular Technology Conference

作者： Chanfei Wang Tiejun Lv Hui Gao Anzhong Hu Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education School of Information and Communication Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781479944811

In this paper, two near-optimal detectors based on the convex optimization algorithm are proposed for multiuser detection (MUD) in the ultra-wide bandwidth (UWB) systems. The first detector performs semidefinite relaxation (SDR) to approximate the optimum multiuser detection (OMD) which is a nondeterministic polynomial time hard (NP-hard) problem. When the cutting planes generation algorithm is employed to strengthen the relaxation of the SDR, a tight MUD detector for combinatorial optimization is obtained by adding triangle inequalities to the well-known SDR in strict feasible region. Simulations demonstrate that the semidefinite programming (SDP) approaches can provide bit error rate (BER) performance close to the OMD efficiently using the interior point method, and the tight detector provides a better BER performance than the previous detector with a slightly higher complexity.

关键词： combinatorial mathematics computational complexity error statistics mathematical programming multiuser detection relaxation ultra wideband communication BER MUD detector NP-hard problem OMD SDP SDR UWB multiuser detection systems bit error rate combinatorial optimization convex optimization algorithm generation algorithm near-optimal detectors nondeterministic polynomial time hard problem optimum multiuser detection semidefinite programming semidefinite relaxation ultra-wide bandwidth systems Bit error rate Complexity theory Detectors Multiuser detection optimization Programming Vectors Bit error rate Multiuser detection SDPR gene OMD gene combinatorial mathematics Nondeterministic polynomial-time hard Ultra wideband communication Service Discovery Protocol optimization algorithms Complexity theory Programming complexity classes detector relaxation Relaxation

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Trajectory optimization of Flapping Wings Modeled as a Three Degree-of-Freedoms Oscillation System

Trajectory Optimization of Flapping Wings Modeled as a Three...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Yi Qin Bo Cheng Xinyan Deng School of Mechanical Engineering Purdue University West Lafayette IN 47906 USA

ISBN: (纸本)9781479969357

Insects are able to create complex wing trajectories using power and steering muscles attached to the wing/thorax oscillation system. In this paper, we propose a dynamic model for such an oscillation system, and study its dynamic behavior. In particular, we model the wing as a rigid body with three degrees of freedom. The power muscle is modeled by a torque actuator and a torsional spring creating basic wing flapping (stroke) motion. Torsional springs at the wing longitudinal rotation and deviation axes are used to mimic the steering muscles. Aerodynamic forces and moments are calculated using blade-element analysis and quasi-steady aerodynamic model. Dimensional analysis shows that the dynamic behavior of the system is determined by the three spring coefficients and the input torque coefficient, and is characterized by four basic patterns of wing trajectories. By exploring the parameter space of these coefficients, we found that the wing trajectory that most similar to those of a real insect generates the best lift and power loading. Furthermore, a hybrid optimization algorithm is implemented to find the optimal stiffness coefficients that maximize the power loading. Notably, the results also indicate that the flapping trajectories with out-of-plane deviation achieve a better aerodynamic performance than those without it. The oscillatory property of this system does not only explain how insects use flight muscles to tune wing kinematics, but also allows for design simplifications of the wing driving mechanism of flapping micro air vehicles.

关键词： oscillatory system trajectory optimization Wings three degrees of freedom Flapping wings Energy sources Insecta aerodynamic performance Flight muscle trajectory system behavior optimization algorithms

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optimization of Water Management in Shale Gas Production Process

Optimization of Water Management in Shale Gas Production Pro...

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IEEE Annual Conference on Decision and Control

作者： Jiyao Gao Fengqi You Department of Chemical & Biological Engineering Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781467360890

We propose an optimization model for the design and operation of the water management system in shale gas production process. The objective is to maximize the profit per unit freshwater consumption. This model is formulated as a mixed-integer linear fractional programming (MILFP) problem, which takes into account both the economic performance and water-use efficiency associated with the shale gas production. We also present tailored optimization algorithms for efficiently solving the MILFP problem, which results from the water management optimization model. We apply the proposed optimization model to a long-term spatially explicit case study. The optimal results show that the net profit for shale gas production per unit freshwater consumption after water treatment is $1,756 per thousand barrels of freshwater. The results also indicate that an efficient water management strategy should be a combination of different water management options, including centralized wastewater treatment, underground disposal, and onsite treatment.

关键词： Water Management water treatment system Gas production model design sewage treatment optimization algorithms underground disposal Water Treatment

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Towards Wind Farm Performance optimization through Empirical Models

Towards Wind Farm Performance Optimization through Empirical...

引用

IEEE Aerospace Conference

作者： Scott C. Evans Zhanpan Zhang Satish Iyengar Jianhui Chen John Hilton Peter Gregg David Eldridge Mark Jonkhof Colin McCulloch Mohammad Shokoohi-Yekta GE Global Research GE Power and Water Renewables University of California Riverside

ISBN: (纸本)9781479916191

Wind Turbine performance improvement measurements are challenging, especially when improvements affect air flow to the nacelle anemometer sensor which is often used to baseline performance. Uncertainty in this area can impede optimization of wind farms by making it difficult to 1) show the benefit of upgrades to individual turbines, 2) jointly optimize wind turbine performance in a farm, and 3) validate the effects of optimization algorithms - particularly farm level algorithms and strategies that mitigate waking affects. In this paper we introduce methods that augment traditional methods for baselining wind turbine performance using multi-feature estimation based on empirical data and present a method for normalizing AEP uncertainty estimates. This innovative method does not rely solely on nacelle anemometer estimates or expensive additional sensors, as has been the historical approach but can leverage these trusted sensors if they are available. Future directions for whole farm optimizations are discussed.

关键词： Machine Learning Statistical Learning Wind Farm optimization Wind Turbine Power Curve Statistical learning Wind farms empirical models Wind Energy Conversion Systems Artificial Intelligence Machine Learning Turbine performance Anemometers Farms optimization algorithms Sensors empirical data air flow

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A frequency set adaptive optimization algorithm for differential frequency hopping network based on cognitive radio and Latin squares

A frequency set adaptive optimization algorithm for differen...

引用

10th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2014)

作者： Zhuo Cheng Shu Wang Dianhong Wang Shu Yan The School of Machinery and Electronic Information China University of Geosciences Wuhan 430074 China Dept. of Electronics & Information Engineering Huazhong University of Science & Technology Wuhan 430074 China

ISBN: (纸本)9781510804166

Differential frequency hopping (DFH) was believed to be an effective FH technique for increasing data rate of FH communication system. Cognitive radio (CR) users can use the CR technology to sense the surrounding RF environment, search for available spectrum resources and access spectrum dynamically. The cognitive radio technology and applied mathematics are introduced in DFH. And the Latin squares based frequency set adaptive optimization (LS-FSAO) algorithm is proposed. In short, the frequency set is divided into many frequency micro-sets after the spectrum sensing, and the micro-sets are assigned to DFH users with dynamic Latin squares. The users' frequency micro-sets are dissimilar during a same time slot to cut down the Multiple Access Interference (MAI), Partial Band Jamming (PBJ) and Multi-Tone Jamming (MTJ). The scenario simulations of the LS-FSAO based DFH network and the traditional DFH are performed, respectively. The results show that the LS-FSAO DFH can obtain favorable network performance.

关键词： Cognitive Radio Differential Frequency Hopping Latin Squares Magic square Cognitive radio optimization algorithms Frequency hopping Latin adaptive optimization Applied mathematics

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A routing cooperative selection method based on ant colony optimization algorithm

A routing cooperative selection method based on ant colony o...

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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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