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检索条件"主题词=Optimization algorithms"

共 3648 条记录，以下是91-100 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...

引用

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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FRAM EVALUATION AS UNIFIED MEMORY FOR CONVEX optimization algorithms 6

FRAM EVALUATION AS UNIFIED MEMORY FOR CONVEX OPTIMIZATION AL...

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6th European Embedded Design in Education and Research Conference (EDERC)

作者： Gionata, Cimini Alberto, Bemporad Gianluca, Ippoliti Sauro, Longhi Univ Politecn Marche I-60131 Ancona Italy IMT Inst Adv Studies I-55100 Lucca Italy

ISBN: (纸本)9781479968435

Ferroelectric Random Access Memory (FRAM) by Texas Instruments (TI) is a non-volatile memory which allows lower power and faster data throughput compared to other nonvolatile solutions. These features have accelerated the interest in this technology as the future of embedded unified memory, in particular in data logging, remote sensing and Wireless Sensor Network (WSN). The application of Model Predictive Control (MPC) in WSN has gained lot of attention in the last years and it requires solving convex optimization problems in real-time. In this paper several convex optimization algorithms have been implemented and compared on a FRAM-based MSP-EXP430FR5739 node by TI, to evaluate its suitability in extending the potentialities of onboard volatile Static Random Access Memory (SRAM) for embedded optimization-based control.

关键词： Convexfunctions Ferroelectricfilms Nonvolatilememory Randomaccessmemory Resourcemanagement Wirelesscommunication Wirelesssensornetworks Wireless sensor networks Static random access storage WSN gene optimization algorithms Titanium Thallium Nonvolatile memory LOW POWER Memory Memory Ferroelectric RAM data throughput

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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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Modeling of Missing Data Prediction: Computational Intelligence and optimization algorithms

Modeling of Missing Data Prediction: Computational Intellige...

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Leke, Collins Twala, Bhekisipho Marwala, Tshilidzi Univ Johannesburg Dept Elect & Elect Engn Sci Johannesburg South Africa

ISBN: (纸本)9781479938407

Four optimization algorithms (genetic algorithm, simulated annealing, particle swarm optimization and random forest) were applied with an MLP based auto associative neural network on two classification datasets and one prediction dataset. This work was undertaken to investigate the effectiveness of using auto associative neural networks and optimization algorithms in missing data prediction and classification tasks. If performed appropriately, computational intelligence and optimization algorithm systems could lead to consistent, accurate and trustworthy predictions and classifications resulting in more adequate decisions. The results reveal GA, SA and PSO to be more efficient when compared to RF in terms of predicting the forest area to be affected by fire. GA, SA, and PSO had the same accuracy of 93.3%, while RF showed 92.99% accuracy. For the classification problems, RF showed 93.66% and 92.11% accuracy on the German credit and Heart disease datasets respectively, outperforming GA, SA and PSO.

关键词： optimization algorithms auto-associative neural networks prediction classification missing data

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Ant Colony optimization algorithms for Wireless Network Planning Problem Solving

Ant Colony Optimization Algorithms for Wireless Network Plan...

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International Conference on Stability and Control Processes in Memory of V.I. Zubov (SCP)

作者： Skakov, Evgenii Malysh, Vladimir Lipetsk State Pedag Univ Fac Phys Math & Comp Sci Lipetsk Russia

ISBN: (纸本)9781467376983

Three modifications of the ant colony optimization method for solving the base station location problem for creating a wireless network is introduced in the article. By means of computer simulation the influence of the input parameters to the speed of finding a problem solution is determined. It also was detected the best kind of the proposed ant colony optimization algorithms applied to the task.

关键词： Ant colony optimization Wireless networks input parameter Problem solving optimization algorithms 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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An Orchestrated Survey on T-Way Test Case Generation Strategies Based on optimization algorithms

An Orchestrated Survey on <i>T</i>-Way Test Case Generation ...

引用

8th International Conference on Robotic, Vision, Signal Processing and Power Applications (RoViSP)

作者： Al-Sewari, AbdulRahman A. Zamli, Kamal Z. Univ Malaysia Pahang Software Engn Dept Fac Comp Syst & Software Engn Kuantan 26300 Pahang Malaysia

ISBN: (纸本)9789814585422;9789814585415

The test case construction is amongst the most labor-intensive tasks and has significant influence on the effectiveness and efficiency in software testing. Due to the market needed for diverse types of tests, recently, several number of t-way testing strategies (where t indicates the interaction strengths) have been developed adopting different approaches Algebraic, Pure computational, and optimization algorithms (OpA). This paper presents an orchestrated survey of the existing OpA t-way strategies as Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Algorithm (ACA), Particle Swarm optimization based strategy (PSTG), and Harmony Search Strategy (HSS). The results demonstrate the strength and the limitations of each strategy, thereby highlighting possible research for future work in this area.

关键词： T-way testing Test case generation Software and hardware testing optimization algorithms

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A Comprehensive Survey on Dimension Reduction for Medical Big Data Using optimization algorithms 4

A Comprehensive Survey on Dimension Reduction for Medical Bi...

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4th International Mobile, Intelligent, and Ubiquitous Computing Conference

作者： Abdelminaam, Diaa Salama Abu Alheijat, Ahmed Taha, Mohamed Benha Univ Fac Comp & Artificial Intelligence Banha Egypt Misr Int Univ Fac Comp Sci Cairo Egypt Obour High Inst Informat Dept Comp Sci Cairo Egypt

ISBN: (纸本)9798350367782;9798350367775

This paper surveys dimension reduction techniques in medical big data using optimization algorithms to address challenges like computational inefficiency, overfitting, and interpretability in high-dimensional datasets. As medical data from sources like electronic health records, genomics, and imaging grow, efficient processing is essential for personalized healthcare. The paper explores feature extraction (PCA, LDA) and feature selection methods, emphasizing metaheuristic algorithms like Genetic algorithms (GA), Particle Swarm optimization (PSO), and Ant Colony optimization (ACO). These algorithms enhance machine learning model accuracy by selecting relevant features, reducing computational costs, and handling nonlinear relationships in medical data. Applications in diagnosis, treatment prediction, and disease classification are discussed. Future research aims to integrate various optimization strategies and deep learning for more effective dimensionality reduction in healthcare.

关键词： Dimension Reduction Medical Big Data feature selection optimization algorithms machine learning Meta-heuristics

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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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General structure-based classification of optimization algorithms for an objective comparison 17

General structure-based classification of Optimization Algor...

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International Conference on Electromagnetics in Advanced Applications / IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications

作者： Niccolai, Alessandro Gonano, Carlo Andrea Grimaccia, Francesco Mussetta, Marco Zich, Riccardo Enrico Politecn Milan Via La Masa 34 I-20156 Milan Italy

ISBN: (纸本)9781479978069

The aim of this work is to introduce an effective tool in order to help the EM designer to select the best optimization algorithm through an easy-to-manage classification of Evolutionary algorithms. In fact, choosing the best tool for an application could be really difficult, especially for a user not aware of optimization theory. Here we propose a general analysis for EAs, highlighting their block-structure and classifying them through some objective (non-qualitative) parameters.

关键词： optimization algorithms optimization theory collective agreement evolutionary algorithm BASES(STRUCTURES)

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