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2008 International Conference on Information and Knowledge Engineering, IKE 2008

作者： Ahmad, S. Nazari, A. Abdollahian, M. Zeephongsekul, P. School of Mathematical and Geospatial Sciences RMIT University Melbourne Australia School of Information Technology and Mathematical Sciences University of Ballarat Australia

ISBN: (纸本)1601320752

In this paper we propose fitting Burr distributions to continuous positively skewed data. The proportion of nonconformance (PNC) for process measurements is then obtained by using Burr distribution, rather than through the traditional practice of fitting different distributions to real data. Also, a new approach called hybrid search method is introduced to find parameters of the fitted Burr distribution. The results based on this hybrid search are then compared with the exact proportion of nonconformance of the data. Finally, a case study using real data is presented.

关键词： Burr distribution hybrid search algorithm Process capability Proportion of nonconformance for non-normal process

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On-line resources allocation for ATM networks with rerouting

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COMPUTERS & OPERATIONS REsearch 2006年第10期33卷 2891-2917页

作者： Loudni, S Boizumault, P David, P Univ Caen GREYC CNRS UMR 6072 F-14032 Caen France Ecole Mines Nantes F-44307 Nantes 3 France

This paper presents an application we developed for France Telecom R&D to solve a difficult real-life network problem. The problem takes place in an Asynchronous Transfer Mode (ATM) network administration context and consists in planning demands of connection over a period of 1 year. A new demand is accepted if both bandwidth and Quality of Service (QoS) requirements are satisfied. Demands are not known prior to the assignment and must be performed on-line according to their arrival. Moreover, the acceptance or the reject of a demand must be decided within a given time of 1 min. First, we look for a route satisfying the new demand. In case of failure, we try to reroute, some already accepted connections in order to satisfy this new demand. Rerouting has been modelled as a Weighted Constraint Satisfaction Problem (WCSP) and solved by VNS/LDS + CP, a hybrid method well suited for solving WCSPS in on-line contexts. Experiments show that our rerouting enables to accept an average of 67% of demands that would be rejected otherwise. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： network routing ATM Quality of Service Dijkstra shortest path algorithm anytime context constraint satisfaction problem WCSP hybrid search algorithm VNS LDS

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Evolutionary optimization with Markov random field prior

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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2004年第6期8卷 567-579页

作者： Wang, X Wang, H Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

This paper discusses an evolutionary algorithm in which the constituent variables of a solution are modeled by a Markov random field (MRF). We maintain a population of potential solutions. at every generation and for each solution a fitness value is calculated. The evolution, however, is not achieved through genetic recombination. Instead, each variable in a solution will be updated by sampling from its probability distribution. According to the MRF prior, local exploitation is encoded in the conditional probabilities. For evolutionary exploration, we estimate the probabilities as fitness-weighted statistics. These two kinds of search are combined smoothly in our algorithm. We compare it with two representative algorithms [iterated conditional modes (ICM) and simulated annealing (SA)] on noisy and textured image segmentation. Remarkable performance is observed.

关键词： combinatorial optimization estimation of distribution algorithms evolutionary computation genetic algorithms (GAs) hybrid search algorithm image segmentation Markov random fields (MRF)

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Flux control of consequent-pole hybrid excitation motors in constant power region to achieve both high efficiency and fast convergence speed

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JOURNAL OF POWER ELECTRONICS 2022年第1期22卷 10-21页

作者： Lu, Xingchi Fan, Ying Chen, Junlei Lei, Yutong Southeast Univ Sch Elect Engn Nanjing Peoples R China

This paper proposes a new flux control strategy for consequent-pole brushless hybrid excitation (CPBHE) machines to achieve a high efficiency and a fast convergence. Based on an analysis of the mathematical model of a CPBHE machine, a loss model of the CPBHE machine is derived, which demonstrates the feasibility of adopting d-axis flux to search for the optimal efficiency point. Furthermore, to improve the convergence speed of the online search algorithm and to make it suitable for the frequently varying operating conditions of electric vehicles (EVs), an adaptive step search algorithm based on the margin of the voltage limit combined with the offline table lookup method is proposed. Experimental results show that the proposed algorithm can optimize the efficiency of a motor system in the flux-weakening region and that it features a fast optimization process that makes it suitable for EV drives.

关键词： Consequent-pole brushless hybrid excitation (CPBHE) machine Efficiency optimization Online search algorithm Table lookup hybrid search algorithm

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Stochastic L-system inference from multiple string sequence inputs

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SOFT COMPUTING 2023年第10期27卷 6783-6798页

作者： Bernard, Jason McQuillan, Ian McMaster Univ Dept Surg Hamilton ON Canada Univ Saskatchewan Dept Comp Sci Saskatoon SK Canada

Lindenmayer systems (L-systems) are a grammar system that consists of string rewriting rules. The rules replace every symbol in a string in parallel with a successor to produce the next string, and this procedure iterates. In a stochastic context free L-system (S0L-system), every symbol may have one or more rewriting rule, each with an associated probability of selection. Properly constructed rewriting rules have been found to be useful for modeling and simulating some natural and human engineered processes where each derived string describes a step in the simulation. Typically, processes are modeled by experts who meticulously construct the rules based on measurements or domain knowledge of the process. This paper presents an automated approach to finding stochastic L-systems, given a set of string sequences as input. The implemented tool is called the Plant Model Inference Tool for S0L-systems or PMIT-S0L. PMIT-S0L is evaluated using 960 procedurally generated S0L-systems in a test suite, which are each used to generate input strings, and PMIT-S0L is then used to infer the system from only the sequences. The evaluation shows that PMIT-S0L infers S0L-systems with up to 9 rewriting rules each in under 12 hours. Additionally, it is found that 3 sequences of strings are sufficient to find the correct original rewriting rules in 100% of the cases in the test suite, and 6 sequences of strings reduce the difference in the associated probabilities to approximately 1% or less.

关键词： Lindenmayer systems Plant modelling Model inference Stochastic simulations hybrid search algorithm

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Effects of multiple threshold values for PN code acquisition in DS-CDMA systems

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ELECTRONICS LETTERS 2001年第6期37卷 363-365页

作者： Lee, S Kim, J Yonsei Univ Dept Elect & Elect Engn Seodaemun Gu Seoul 120749 South Korea

A decision method using multiple threshold values for PN code acquisition in DS-CDMA systems is described. This technique is applied to a conventional hybrid search algorithm and analysed in terms of the probability of detection and false alarm. Simulation results show that the proposed scheme outperforms the conventional scheme in terms of detection probability because multiple threshold values mitigate any possible decline in performance caused bq the use of a single threshold.

关键词： Multiple access communication hybrid search algorithm Signal detection false alarm spread spectrum communication PN code acquisition decision method signal detection probability of detection probability code division multiple access multiple threshold values Other topics in statistics DS-CDMA systems

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5 GHz all-digital delay-locked loop for future memory systems beyond double data rate 4 synchronous dynamic random access memory

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ELECTRONICS LETTERS 2015年第24期51卷 1973-1974页

作者： Lee, Dongyeol Kim, Jongsun Hongik Univ Elect & Elect Engn Seoul 121791 South Korea

A new low-power, fast-locking, all-digital delay-locked loop (DLL) that uses a disposable time-to-digital converter (TDC) is presented for future memory systems beyond double data rate 4. To achieve fast locking and high-frequency operation, the proposed DLL utilises a new hybrid (TDC + binary + sequential) search algorithm that results in a fast locking time of 11 clock cycles without the false lock and harmonic lock problems. By minimising the intrinsic delay of the digital delay line, the proposed DLL achieves an operating frequency range of 1.5-5.0 GHz which is higher than that of the current state-of-the-art all-digital DLLs. The DLL is fabricated in a 65 nm CMOS process and it achieves a peak-to-peak (p-p) output clock jitter of 14 ps (with a p-p input clock jitter of 8 ps) at 5 GHz. The DLL consumes 6.9 mW at 1 V and occupies an active area of 0.025 mm(2).

关键词： random-access storage time-digital conversion search problems clocks CMOS memory circuits timing jitter synchronisation low-power electronics memory systems synchronous dynamic random access memory all-digital delay-locked loop low-power DLL fast-locking DLL time-to-digital converter hybrid search algorithm TDC search algorithm binary search algorithm sequential search algorithm clock cycles harmonic lock problems intrinsic delay digital delay line CMOS process peak-to-peak output clock jitter p-p output clock jitter frequency 1 5 GHz to 5 0 GHz size 65 nm power 6 9 mW voltage 1 V size 0 025 mm

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A Robotic Swarm searching Method for Unknown Environments Based on Foraging Behaviors

A Robotic Swarm Searching Method for Unknown Environments Ba...

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4th International Conference of Bionic Engineering (ICBE 2013)

作者： Li, Shoutao Li, Lina Lee, Gordon Jilin Univ Coll Commun Engn Changchun 130023 Jilin Province Peoples R China San Diego State Univ Dept Elect & Comp Engn San Diego CA USA

ISBN: (纸本)9783037859322

This paper proposes a novel method for a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics that are inspired by the foraging behavior in nature. First, the searching area is divided into several sub-regions using a target utility function, from which each robot can identify an area that should be initially searched. Then, a predatory strategy is used for searching in the sub-regions;this hybrid approach integrates a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a robot cannot find any target information in the sub-region, it uses a global random search algorithm;if the robot finds any target information in the sub-region, the DPSO search algorithm is used for a local search. The particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism as the searching progresses until the robots find the target position. Then, the robots fall back to a random searching mode and continue to search for other places that were not searched previously. In this searching strategy, the robots alternate between two searching algorithms until the whole sub-area is covered. During the searching process, the robots use a local communication mechanism to share map information and the DPSO parameters to reduce the communication burden and overcome hardware limitations.

关键词： target utility function hybrid search algorithm local communication

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Classifier Ensembles Optimization Guided by Population Oracle

Classifier Ensembles Optimization Guided by Population Oracl...

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IEEE Congress on Evolutionary Computation (CEC)

作者： dos Santos, Eulanda M. Sabourin, Robert Univ Fed Amazonas Manaus Amazonas Brazil Ecole Technol Super Montreal PQ Canada

ISBN: (纸本)9781424478354

Dynamic classifier ensemble selection is focused on selecting the most confident classifier ensemble to predict the class of a particular test pattern. The overproduce-and-choose strategy is a dynamic classifier ensemble selection method which is divided into optimization and dynamic selection phases. The first phase involves the test of different candidate ensembles in order to produce a population composed of the highest performing candidate ensembles. Then, the second phase calculates the domain of expertise of each candidate ensemble to pick up the solution with highest degree of certainty of its decision to classify the unknown test samples. It has been shown that the optimization phase decreases oracle, the upper bound of dynamic selection processes. In this paper we propose a hybrid algorithm to perform the optimization phase of overproduce-and-choose strategy. The proposed algorithm combines stochastic initialization of candidate ensembles of different sizes, with the traditional forward search greedy method. The objective is to apply oracle as search criterion during the optimization phase. We show experimentally that choosing the population of classifier ensembles taking into account the population oracle leads to increase the upper bound of the dynamic selection phase. Moreover, experimental results conducted to compare the proposed method to a multi-objective genetic algorithm (MOGA), demonstrate that our method outperforms MOGA on generating population of candidate ensembles with higher oracle rates.

关键词： Dynamic classifier ensemble selection hybrid search algorithm multi-objective genetic algorithm pattern recognition

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Formation Deployment of Cooperative Source Seeking by Multiple Robots: algorithms and Experiments 31

Formation Deployment of Cooperative Source Seeking by Multip...

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31st Chinese Control And Decision Conference (CCDC)

作者： Zhu, Dezheng Cao, Meng China Elect Technol Grp Corp Res Inst 28 Nanjing 210007 Peoples R China

ISBN: (纸本)9781728101057

In order to deploy multi-robot into a 2-D desired formation during the seeking process, this paper proposes a hybrid seeking algorithm with the formation deployment. Firstly, a reaction-advection-diffusion equation is quoted to describe the movement of multiple mobile robots, 1-D formation deployment algorithm is introduced and expended to 2-D application. And then combines with the extreme seeking algorithm to obtain the hybrid seeking algorithm. Based on the improved extremum seeking algorithm and the 2-D formation deployment algorithm, a multi-robot hybrid seeking algorithm with formation deployment is proposed. To simplify other robots' following, a virtual trajectory of the leader robot is obtained according to its searching features. The robots' behavior is decomposed into searching behavior and formation deployment behavior. The condition and the method of changing these behaviors' weights online are provided. With the algorithm, multi-robot can deploy into a desired 2-D formation during seeking process. Simulation results with different initial positions and different platforms are analyzed to verify the convergence of the multi-robot's hybrid seeking algorithm, and the convergence is independent of the multi-robot's initial positions.

关键词： multi-robot extreme seeking algorithm formation deployment hybrid search algorithm

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