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检索条件"主题词=Optimization Algorithms"

共 3923 条记录，以下是101-110 订阅

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A SyR and IPM machine design methodology assisted by optimization algorithms

A SyR and IPM machine design methodology assisted by optimiz...

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IEEE Energy Conversion Congress and Exposition (ECCE)

作者： Cupertino, F. Pellegrino, G. M. Armando, E. Gerada, C. Politecn Bari DEE Bari Italy

ISBN: (纸本)9781467308014

The design optimization of synchronous reluctance (SyR) machine and its extension to internal permanent magnet (IPM) motors for wide speed ranges is considered in this paper by means of a Finite Element Analysis-based multi-objective genetic algorithm (MOGA). The paper is focused on the rotor design, that is controversial key aspect of the design of high saliency SyR and IPM machines, due to the difficult modeling dominated by magnetic saturation. A three step procedure is presented, to obtain a starting SyR design with the optimal torque versus torque ripple compromise and then properly include PMs into the SyR geometry, given the desired constant power speed range of the final IPM machine. The designed rotors have been extensively analyzed by computer simulations and two SyR prototypes have been realized to demonstrate the feasibility of the design procedure.

关键词： design process optimization algorithms Integrated Pest Management Optimal design speed range mechanical engineering Equipment Design Pavement management system machine Rotors Computer Simulation

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Hybrid optimization algorithms Resembling the Life Cycles of Organisms of Phylum Cnidaria

Hybrid Optimization Algorithms Resembling the Life Cycles of...

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Int Conference Adv Elect Comp Commun ICAECC

作者： Premaratne, Upeka Halgamuge, Saman Univ Moratuwa Dept Elect & Telecommun Engn Katubedda 10400 Moratuwa Sri Lanka Univ Melbourne Dept Mech Engn Melbourne Vic 3010 Australia

ISBN: (纸本)9781479954964

The biological world is an ideal place for seeking inspiration for developing mathematical optimization algorithms. In this paper we propose two hybrid stochastic optimization algorithms that bear resemblance to the sexual reproduction cycle of Jellyfish and asexual reproductive cycle of species of Hydra. The performance of these two algorithms are investigated against other common optimization algorithms on a set of benchmark optimization problems. The results show that the proposed algorithms perform well.

关键词： optimization algorithms Biological Inspiration Hybrid optimization algorithms Jellyfish Reproduction Hydra Asexual Reproduction

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Clustering and optimization algorithms to Enable Reliable 6G Mobile Molecular Communications 12th

Clustering and Optimization Algorithms to Enable Reliable 6G...

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12th World Conference on Information Systems and Technologies (WorldCIST)

作者： Bordel, Borja Alcarria, Ramon Robles, Tomas Univ Politecn Madrid Madrid Spain

ISBN: (纸本)9783031602269;9783031602276

Molecular communications are envisioned to transform medicine and environmental sciences, but currently only small, isolated networks have been deployed. It is essential, then, to develop new mechanisms to enable information flow from remote users to nanometric biological machines through next-generation networks, such as 6G mobile technologies. 6G mobile networks are characterized by an extreme Quality-of-Service, but in the context of molecular communications, two requirements turn critical: ultra-massive and extremely reliable communications. Molecular communications are simplex, so there is typically no channel to transmit acknowledgment messages. Furthermore, several nanometric receptors concentrated in just some square micrometers are an ultra-massive device density for 6G base stations. In this paper, we propose a computational algorithm to make reliable and massive 6G mobile molecular communications feasible. The proposed algorithm employs clustering to create a real-time map with the positions of the biological nanometric machines, and particle swarm optimization to track the identity of the different machines while slowly moving. To handle ultra-massive density, clustering operates by defining which magnetic particles used as communication interface belong to the same biological machine. While the optimization mechanism considers the current and previous clustering results and a probabilistic model to determine the identity of each cell. Reliability is achieved by an acknowledgment message generated by a 6G transceiver when the biological machines reach the expected destination. Simulation tools are employed to validate the proposed solution. Results show that the identification error is less than 15%, and the reliability achieves a probability of up to 90%.

关键词： optimization algorithms clustering 6G communications molecular communications identity tracking probabilistic models

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Fully Informed Swarm optimization algorithms: Basic Concepts, Variants and Experimental Evaluation

Fully Informed Swarm Optimization Algorithms: Basic Concepts...

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Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Lukasik, Szymon Kowalski, Piotr A. Cracow Univ Technol Dept Automat Control & IT PL-31155 Krakow Poland Polish Acad Sci Syst Res Inst PL-01447 Warsaw Poland

ISBN: (纸本)9788360810583

Particle swarm optimization constitutes currently one of the most important nature-inspired metaheuristics, used successfully for both combinatorial and continuous problems. Its popularity has stimulated the emergence of various variants of swarm-inspired techniques, based in part on the concept of pair-wise communication of numerous swarm members solving optimization problem in hand. This paper overviews some examples of such techniques, namely Fully Informed Particle Swarm optimization (FIPSO), Firefly Algorithm (FA) and Glowworm Swarm optimization (GSO). It underlines similarities and differences among them and studies their practical features. Performance of those algorithms is also evaluated over a set of benchmark instances. Finally, some concluding remarks regarding the choice of suitable problem-oriented optimization technique along with areas of possible improvements are given as well.

关键词： Cost function Heuristic algorithms Particle swarm optimization Space exploration Topology Vectors Particle swarm optimization Space Exploration Heuristic algorithms Cost functions topology optimization algorithms variants Cloning Vectors

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Applicability of Soft Computing and optimization algorithms in Software Testing and Metrics - A Brief Review 8th

Applicability of Soft Computing and Optimization Algorithms ...

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8th International Conference on Soft Computing and Pattern Recognition (SoCPaR) / 8th International Conference on Computational Aspects of Social Networks (CASoN)

作者： Sharma, Deepak Chandra, Pravin Guru Gobind Singh Indraprastha Univ Univ Sch Informat & Commun Technol Delhi 110078 India

ISBN: (纸本)9783319606187;9783319606170

In spite of many years of work by scientists and specialists on various software qualities, testing stays one of the most broadly honed and concentrated on methodologies for evaluating and improving software quality. Our objective, in this paper, is to present how optimization techniques provide solutions to different and difficult issues in different areas of software engineering. optimization algorithms are mathematical procedures, which intends to best optimal results for the defect, fault, failure to accomplish tractability, strength, and low arrangement cost. In this paper, a comprehensive overview of software testing and metrics based on soft computing and optimization techniques is presented. In this survey, we try to explain some major problems like defect prediction, software fault prediction and their solutions by soft computing and optimization algorithms. The paper presents an overview of the usage of Mathematical optimization algorithms and soft computing approaches.

关键词： optimization algorithms Soft computing Software testing Metrics Software fault prediction

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Graph-based indoor navigation system using BIM data and optimization algorithms 20

Graph-based indoor navigation system using BIM data and opti...

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20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA)

作者： Rachidi, Yusra Abouelaziz, Ilyass CESI LINEACT Lab UR 7527 Dijon France Informat Sci Sch ESI Lyrica Labs Rabat Morocco

ISBN: (纸本)9798350319439

This paper presents a smart navigation system that uses Building Information Modeling (BIM) data extracted from Industry Foundation Classes (IFC) files to generate a graph network for efficient path planning. The proposed method focuses on the construction of a graph networks, and the application of optimization algorithms to estimate optimal paths in a building environment. First, we extract relevant information about the building such as spaces, doors. This data serves to construct a graph network that represents the connectivity and relationships between different spaces in the building. Once the graph network is established, optimization algorithms are used to estimate optimal paths for navigation. The proposed method aims to provide accurate and efficient path recommendations, enhancing navigation in the building environment. The performance of our method is evaluated using a larger graph network derived from a real-world building. The results demonstrate the potential of the smart navigation system in achieving reliable path planning.

关键词： Indoor navigation system Optimal path Building information modeling optimization algorithms

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Wideband and polarization-independent silicon waveguide to plasmonic waveguide mode converter based on optimization algorithms 6

Wideband and polarization-independent silicon waveguide to p...

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6th Symposium on Novel Optoelectronic Detection Technology and Applications

作者： Liu, ZunWei Zhang, Tian Dai, Jian Xu, Kun Beijing Univ Posts & Telecommun State Key Lab Informat Photon & Opt Commun Beijing 100876 Peoples R China

ISBN: (纸本)9781510637054

Conventional silicon optical waveguide can be effectively coupled to plasmonic waveguide, but there is no structure of comparable coupling efficiency, wide optical bandwidth and polarization independence to convert light from silicon waveguide to metal-dielectric-metal (MDM) waveguide. In this paper, we investigate a novel mode converter based on the embedded coding metamaterials to effectively convert the TE/TM mode in a silicon waveguide to the SPPs mode. We use some optimization methods (genetic algorithm, particle swarm optimization, multi-traversal direct-binary search and simulated annealing) in the design of coding metamaterials to improve the performance metrics. In order to obtain better results, we change the value of different parameters under the control of a single variable to study its influence on the structure of the design. The simulation results have been demonstrated numerically that high transmission efficiency is up to 93% and the bandwidth can cover from 1450 nm to 1650 nm, the converter can perform polarization-invariant conversion as well. Compared with the previous researches, we not only propose a high-performance mode converter but also introduce an efficient algorithm for the inverse design of coding metamaterials.

关键词： Mode converter optimization algorithms inverse design plasmonics embedded coding metamaterials

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Development of optimization algorithms for electromagnetic characterization in free space 17

Development of optimization algorithms for electromagnetic c...

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17th European Conference on Antennas and Propagation (EuCAP)

作者： Cidras Estevez, Jose Ramos Somolinos, David Plaza Gallardo, Borja Poyatos Martinez, David Natl Inst Aerosp Technol INTA Torrejon De Ardoz Madrid Spain

ISBN: (纸本)9788831299077

In recent years, in the aerospace industry, there has been a trend based on replacing the classic metallic materials with new advanced materials such as carbon fiber composites (CFC), fiberglass, etc. Due to this, the electromagnetic (EM) characterization of these new materials is essential to maintain safety and EM compatibility. This article will focus on the free space measurement technique, from which a series of optimization algorithms have been developed, allowing the extraction of permittivity and permeability of materials in a frequency range up to 40 GHz using the Time-Domain Gating from a Vector Network Analyzer (VNA).

关键词： optimization algorithms free-space method scattering parameters time-domain gating material characterization non-destructive testing permeability permittivity

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Comparison of Different optimization algorithms with Two Stage Initialization for PID Controller Tuning in Automatic Voltage Regulator System 4

Comparison of Different Optimization Algorithms with Two Sta...

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IEEE Students' Technology Symposium (TechSym)

作者： Puralachetty, Manasa Madhavi Pamula, Vinay Kumar Akula, Venkata Naresh Babu JNTUK UCEK Dept ECE Kakinada 533003 India MIC Coll Technol Dept EEE Kanchikacherla 521180 India

ISBN: (纸本)9781509051632

PID controller tuning plays a very important role in the proper functioning of the plant in which the controller is incorporated. A modification to the already existing algorithms like the differential evolution (DE), particle swarm optimization (PSO) and teaching-learning-based optimization (TLBO) algorithms is done in this paper. The modification is done in the initialization method and is called the two stage initialization (TSI). In TSI, the population vector generation is done randomly in two stages. Then the newly generated population vector from TSI would go through the rest of the phases involved in the algorithms. Further, these two stage initialized optimization algorithms and their original versions are used to tune the PID controller for automatic voltage regulator (AVR) system. Comparison of the results so obtained due to the application of six optimization algorithms out of which three are already existing ones and the other three are their TSI versions to PID-AVR system is also done. It can be realized that TSI helps the existing algorithms to have greater convergence rate and also to converge at a lesser minimum value of the objective function.

关键词： optimization algorithms PID controller Automatic voltage regulator Two stage initialization DE PSO TLBO

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Mathematical modelling and comparisons of four heuristic optimization algorithms for WCDMA radio network planning

Mathematical modelling and comparisons of four heuristic opt...

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8th International Conference on Transparent Optical Networks

作者： Zhang, Jie Yang, Jun Aydin, Mehmet E. Wu, Joyce Y. Univ Luton Dept Comp & Informat Syst Ctr Wireless Network Design Luton LU1 3JU Beds England

ISBN: (纸本)1424402360

In order to obtain accurate and reliable network planning and optimization results. The characteristics of WCDMA networks such as power control, soft handover (SHO) and the strong couplings between coverage and capacity have to be modelled accurately. These characteristics lead to unprecedented complexity of WCDMA radio network planning and optimisation that has not been seen in previous cellular networks. In this paper, we will present mathematical models that consider the characteristics of WCDMA radio networks. We will also present and compare the performance of four optimisation algorithms based on meta-heuristics that can be used to find solutions for practical WCDMA radio network planning and optimisation.

关键词： WCDMA mathematical modelling radio network planning optimization algorithms

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