Electromagnetic (EM)-driven adjustment of geometry parameters, often referred to as design closure, is nowadays a mandatory stage of antenna design process. It is executed to improve the system performance as much as ...
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ISBN:
(纸本)9788394942175
Electromagnetic (EM)-driven adjustment of geometry parameters, often referred to as design closure, is nowadays a mandatory stage of antenna design process. It is executed to improve the system performance as much as possible while taking into account parameter dependencies that cannot be handled by simpler methods (e.g., theoretical models), typically employed at the initial steps of the antenna development. Unfortunately, EM-based optimization is a time consuming task, especially when the quality of the initial design is poor. This paper proposes a novel framework for accelerated antenna optimization. Our methodology involves a database of previously obtained designs, kriging interpolation models, and an iterative correction scheme for design refinement. The incorporation of pre-existing data permits generation of a good initial design as well as rapid optimization entailing the cost of just a few EM antenna analyses. The technique is demonstrated using a dual-band uniplanar dipole antenna. The structure is optimized within wide ranges of operating frequencies (2 GHz to 3 GHz for the lower band and 4 GHz to 5.5 GHz for the upper band). Benchmarking indicates that the proposed approach exhibits improved computational efficiency and reliability as compared to gradient-based warm-start optimization techniques.
In order to solve the problems of unintuitive expression, incomplete information and inadequate risk identification when using tables and flow charts to plan the core module of China Space Station (CSS) assembly proce...
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A ACO-PSO hybrid algorithm is proposed in order to resolve the path planning problem for deep-sea mining robots. In this study, the environment model was established by Bitmap method, and robot movement was simplified...
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ISBN:
(纸本)9780769533575
A ACO-PSO hybrid algorithm is proposed in order to resolve the path planning problem for deep-sea mining robots. In this study, the environment model was established by Bitmap method, and robot movement was simplified into particle movement by using Framework Space method. Ant colony optimization (ACO) is used to establish the corresponding solution, and some material algorithm steps are set out. Particle swarm optimization (PSO) is applied to optimize the parameters in ACO, and parameters can be selected self-adaptively. Results of simulation experiment demonstrate that this method can satisfy, the precision demand of robots' mining work in deep sea.
The proceedings contain 51 papers. The topics discussed include: analysis of islanding detection in distributed generation using fuzzy logic technique;designing artificial immune system based on clonal selection: usin...
ISBN:
(纸本)9780769551012
The proceedings contain 51 papers. The topics discussed include: analysis of islanding detection in distributed generation using fuzzy logic technique;designing artificial immune system based on clonal selection: using agent-based modeling approach;on the convergence of imperialist competitive algorithm;exploiting bulk agent approach for conflict resolution in multi agent systems;real-time driver gaze direction detection using the 3D triangle model and neural networks;a gini index based elegant decision tree classifier to predict precipitation;improving imperialist competitive algorithm with local search for global optimization;tele-operation of robot using gestures;shear ram speed analysis for gold wire bond shear test;fault tolerance reconstruction for multiple moving objects using reduced camera set;a Petri-net modeling tool and its application on intelligent network;and template matching technique for panoramic image stitching.
This paper proposes a Mahalanobis-Taguchi system variable screening optimization method based on binary quantum behavior particle *** main procedures and methods are as follows, Firstly, the Mahalanobis distance value...
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Scheduling tasks in distributed systems is a classic optimization problem. Cloud computing brings new challenges for traditional scheduling methods due to its characteristics of elasticity. Although the task schedulin...
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ISBN:
(纸本)9781509039449
Scheduling tasks in distributed systems is a classic optimization problem. Cloud computing brings new challenges for traditional scheduling methods due to its characteristics of elasticity. Although the task scheduling problem has been widely studied, there are few heuristics suitable for the cloud environment. In this paper, we propose a cost-effective fault-tolerant scheduling algorithm (CEFT) for real-time tasks in cloud systems. Particle swarm optimization (PSO) is tailored to address the task assignment issue. Primary/backup (P/B) approach is applied to provide fault tolerance for tasks in case of permanent or transient hardware failure. In addition, rescheduling mechanism is put forward to meet the deadline constraints of real-time tasks. simulation experiments are conducted to evaluate the effectiveness of our algorithm. The results show that CEFT makes good balance between low cost and high deadline guarantee ratio.
Advance exergy analysis was applied for optimal design of a shell and tube heat exchanger envisaged as an integral part of a turbo-expander system. Natural gas entering the expansion turbine in a gas-pressure reducing...
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The ant colony optimization (ACO) algorithm is applied to solve the economic operation problems in the plant-level automatic generation control (AGC) of hydropower stations. The built model comprehensively considers m...
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ISBN:
(纸本)9798400716638
The ant colony optimization (ACO) algorithm is applied to solve the economic operation problems in the plant-level automatic generation control (AGC) of hydropower stations. The built model comprehensively considers multiple safe operation constraints such as power balance, unit output constraints, spinning reserve and unit start-up and shutdown time constraints. Meanwhile, the economic load allocation formula derived based on the principle of equal micro-increase rate is embedded in the parallel random search mode to reduce the number of iterations during load allocation. The unit consumption characteristic curve in the experiment is fitted with a quadratic curve based on actual data. The simulation results show that the proposed method has both the randomness of intelligent algorithm search and the stability of traditional algorithms, with fast optimization speed and high accuracy.
Power systems operation is facing great challenges from natural disasters and cyber-attacks. It is critical but also difficult to enhance the reliability and resilience against extreme events. To better response to in...
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ISBN:
(纸本)9781538635964
Power systems operation is facing great challenges from natural disasters and cyber-attacks. It is critical but also difficult to enhance the reliability and resilience against extreme events. To better response to inevitable outages or blackouts, service restoration in distribution networks is important to minimize the disastrous impacts of catastrophic events. The increasing penetration of distributed energy resources (DERs) provides new opportunities to expedite the restoration process. However, the coordination with conventional distribution system control devices and the uncertainty and variability of intermittent renewable energy resources requires new operation and control strategies for distribution service restoration (DSR). This paper develops an optimal bottom-up DSR strategy by coordinating DERs with voltage regulators and capacitor banks. The chanceconstrained (CC) programming approach is used to model the probabilistic output limit of solar radiation and PV generation. The Markov's inequality and Latin hypercube sampling techniques are applied to convert and incorporate the chance constraints into the DSR optimization problem. The CC-DSR problem is formulated as a mixed integer convex programming problem, considering various operational cost functions and bidirectional three-phase unbalanced load flow. simulation results on the modified IEEE 13-node test feeder system demonstrate the effectiveness and flexibility of the bottom-up DSR strategy.
Basic principles of dynamic design were proposed for the characteristics of machine dynamic performance. Take some curved-tooth bevel gear generator as research object. Its dynamic performance was analyzed and structu...
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ISBN:
(纸本)9780878492367
Basic principles of dynamic design were proposed for the characteristics of machine dynamic performance. Take some curved-tooth bevel gear generator as research object. Its dynamic performance was analyzed and structure was optimized through theoretical analysis, finite element method (FEM) simulation and dynamic test analysis. Results show that these principles are suitable for dynamic performance optimization and design of machine tool.
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