Thermal Design of Gas-Fired Cooktop Burners Through ANN

T. Wong, C. Leung
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Abstract

INTRODUCTION Recent advances in the applications of ANN have demonstrated successful cases in time series analysis, data mining, civil engineering, financial analysis, music creation, fishing prediction, production scheduling, intruder detection, etc., making them an important tool for research and development[1]. ANN and evolutionary computation(EC) techniques have been employed successfully in solving real-world problems including those with a temporal component[2]. In another work[3], a hybrid method based on a combination of evolutionary computation and neural network(NN) has been used to predict time series. In the world of databases, various ANN-based strategies have been used for knowledge search and extraction[4]. Intelligent neural systems have been constructed with the aid of genetic algorithm-based EC techniques and these systems have been applied in breast cancer diagnosis[5]. Genetic algorithms(GA) have been applied to develop a general method of selecting the most relevant subset of variables in the field of analytical chemistry to classify apple beverages[6]. New ANN methods enable civil engineers to use computing in different ways. Besides as a tool in urban storm drainage[7], ANN and Genetic Programming(GP) have been implemented in the prediction and modelling of the flow of a typical urban basin [8]. In the latter case, it was shown that these two techniques could be combined in order to design a real-time alarm system for floods or subsidence warning in various types of urban basins. ANN models for consistency, measured by slump, in the case of conventional concrete have also been developed[9]. In a time series prediction of the quarterly values of the medical component of the Consumer Price Index(CPI), the results obtained with both neural and functional networks have been shown to be quite similar[10]. Dimensionality reduction, variable reduction, hybrid networks, normal fuzzy and ANN have been applied to predict bond rating[11]. A recent online survey through the ISI Web of Knowledge using keywords such as " ANN " and " thermal design " would reveal only ten relevant SCI publications[12]. In the area of food processing, ANN was used to predict the maximum or minimum temperature reached in the sample after pressurization and the time needed for thermal re-equilibration[13]. The accurate determination of thermophysical properties of milk is very important for design, simulation, optimization, and control of food processing such as evaporation, heat exchanging, spray drying, and so forth. Generally, polynomial methods are used for prediction of these properties based on empirical correlation to experimental data. However, it was …
基于人工神经网络的燃气炉灶燃烧器热设计
近年来,人工神经网络在时间序列分析、数据挖掘、土木工程、金融分析、音乐创作、捕鱼预测、生产调度、入侵者检测等方面的应用取得了成功,使其成为研究和开发的重要工具。人工神经网络和进化计算(EC)技术已经成功地应用于解决现实世界中的问题,包括那些具有时间分量的问题。在另一项研究[3]中,一种基于进化计算和神经网络(NN)相结合的混合方法被用于预测时间序列。在数据库领域,各种基于人工神经网络的策略已经被用于知识搜索和提取。基于遗传算法的EC技术构建了智能神经系统,并在乳腺癌诊断中得到了应用。遗传算法(GA)已被应用于开发一种通用的方法来选择分析化学领域中最相关的变量子集来对苹果饮料[6]进行分类。新的人工神经网络方法使土木工程师能够以不同的方式使用计算。人工神经网络和遗传规划(GP)除了作为城市暴雨排水的工具外,还被应用于典型城市流域流量的预测和建模。后一种情况表明,这两种技术可以结合起来,以设计一个实时报警系统,用于各种类型的城市盆地的洪水或下沉预警。在常规混凝土的情况下,以坍落度衡量的一致性的人工神经网络模型也已开发出来。在对消费价格指数(CPI)的医疗成分季度值的时间序列预测中,神经网络和功能网络获得的结果已被证明是非常相似的[0]。将降维、变量约简、混合网络、正态模糊和人工神经网络等方法应用于债券评级预测。最近通过ISI知识网进行的一项在线调查使用了“人工神经网络”和“热设计”等关键词,结果显示只有10篇相关的SCI出版物b[12]。在食品加工领域,人工神经网络用于预测加压后样品达到的最高或最低温度以及热再平衡所需的时间[13]。牛奶热物理性质的准确测定对蒸发、换热、喷雾干燥等食品加工过程的设计、模拟、优化和控制具有重要意义。通常,基于经验与实验数据的相关性,使用多项式方法来预测这些特性。然而,它是……
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