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Multi-objective optimization design of a complex building based on an artificial neural network and performance evaluation of algorithms

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ADVANCED ENGINEERING INFORMATICS 2019年 40卷 93-109页

作者： Si, Binghui Wang, Jianguo Yao, Xinyue Shi, Xing Jin, Xing Zhou, Xin Southeast Univ Sch Architecture 2 Si Pai Lou Nanjing 210096 Jiangsu Peoples R China Minist Educ Key Lab Urban & Architectural Heritage Conservat Beijing Peoples R China

While optimization studies focusing on real-world buildings are somewhat limited, many building optimization studies to date have used simple hypothetical buildings for the following three reasons: (1) the shape and form of real buildings are complex and difficult to mathematically describe;(2) computer models built based on real buildings are computationally expensive, which makes the optimization process time-consuming and impractical and (3) although algorithm performance is crucial for achieving effective building performance optimization (BPO), there is a lack of agreement regarding the proper selection of optimization algorithms and algorithm control parameters. This study applied BPO to the design of a newly built complex building. A number of design variables, including the shape of the building's eaves, were optimized to improve building energy efficiency and indoor thermal comfort. Instead of using a detailed simulation model, a surrogate model developed by an artificial neural network (ANN) was used to reduce the computing time. In this study, the performance of four multi-objective algorithms was evaluated by using the proposed performance evaluation criteria to select the best algorithm and parameter values for population size and number of generations. The performance evaluation results of the algorithms implied that NSGA-II (with a population size and number of generations of 40 and 45, respectively) performed the best in the case study. The final optimal solution significantly improves building performance, demonstrating the success of the BPO technique in solving complex building design problems. In addition, the findings on the performance evaluation of the algorithms provide guidance for users regarding the selection of suitable algorithms and parameter settings based on the most important performance criteria.

关键词： Building design optimization Artificial neural network Multi-objective optimization algorithms performance evaluation of algorithms Real-world building design

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Toward objective evaluation of image segmentation algorithms

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2007年第6期29卷 929-944页

作者： Unnikrishnan, Ranjith Pantofaru, Caroline Hebert, Martial Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA

Unsupervised image segmentation is an important component in many image understanding algorithms and practical vision systems. However, evaluation of segmentation algorithms thus far has been largely subjective, leaving a system designer to judge the effectiveness of a technique based only on intuition and results in the form of a few example segmented images. This is largely due to image segmentation being an ill-defined problem - there is no unique ground-truth segmentation of an image against which the output of an algorithm may be compared. This paper demonstrates how a recently proposed measure of similarity, the Normalized Probabilistic Rand (NPR) index, can be used to perform a quantitative comparison between image segmentation algorithms using a hand-labeled set of ground-truth segmentations. We show that the measure allows principled comparisons between segmentations created by different algorithms, as well as segmentations on different images. We outline a procedure for algorithm evaluation through an example evaluation of some familiar algorithms - the mean-shift-based algorithm, an efficient graph-based segmentation algorithm, a hybrid algorithm that combines the strengths of both methods, and expectation maximization. Results are presented on the 300 images in the publicly available Berkeley Segmentation Data Set.

关键词： computer vision image segmentation performance evaluation of algorithms

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Packed AES-GCM Algorithm Suitable for AES/PCLMULQDQ Instructions

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IEEE TRANSACTIONS ON COMPUTERS 2011年第1期60卷 135-138页

作者： Jankowski, Krzysztof Laurent, Pierre Intel Shannon Co Clare Ireland

The level of interest in Galois Counter Mode (GCM) Authenticated Encryption rose significantly within the last few years. GCM is interesting because it is the only authenticated encryption standard that can be implemented in a fully pipelined or parallelized way and it is the most appropriate for encrypting packetized data. McGrew and Viega [1] described (but did not detail) how GHASH can be implemented with more than one multiplier operating in parallel. This paper details how that can be done and shows that, when N multipliers are used, and the multipliers use the approach of multiplying polynomials then applying a modular reduction, a single modular reduction can be used instead on N separate operations. This optimization can be used even when there is a single multiplier, which makes this implementation strategy have a broader appeal. Recently Intel has introduced new ISA instructions into the next generation CPU core, namely: AES family and PCLMULQDQ operating in XMM registers domain. In this paper, we discuss the example implementation of proposed GHASH modifications using above instructions.

关键词： Software data encryption AES GCM performance evaluation of algorithms

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An improved algorithm for the location of heaviest segments in genomic sequences

An improved algorithm for the location of heaviest segments ...

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International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing

作者： Stojanovic, Nikola Univ Texas Arlington Dept Comp Sci & Engn Arlington TX 76019 USA

ISBN: (纸本)9780769537399

The location of heaviest segments in genomic sequences has been effective in the search for diverse groups of regions containing features of interest. Several algorithms have been developed and published to identify either the globally highest scoring segment or all segments scoring the highest in their local environments, some running in time linear with the size of the sequence. In this paper we present a new linear time variant of the algorithm for locating all highest scoring segments in a given sequence, which we believe is better structured, easier to prove correct, and at least as efficient as these previously published.

关键词： Algorithm design and analysis performance evaluation of algorithms biology and genetics

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