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Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing

Reza TEIMOURI, Hamed SOHRABPOOR

《机械工程前沿（英文）》 2013年第8卷第4期页码 429-442 doi: 10.1007/s11465-013-0277-3

摘要：

Electrochemical machining process (ECM) is increasing its importance due to some of the specific advantages which can be exploited during machining operation. The process offers several special privileges such as higher machining rate, better accuracy and control, and wider range of materials that can be machined. Contribution of too many predominate parameters in the process, makes its prediction and selection of optimal values really complex, especially while the process is programmized for machining of hard materials. In the present work in order to investigate effects of electrolyte concentration, electrolyte flow rate, applied voltage and feed rate on material removal rate (MRR) and surface roughness (SR) the adaptive neuro-fuzzy inference systems (ANFIS) have been used for creation predictive models based on experimental observations. Then the ANFIS 3D surfaces have been plotted for analyzing effects of process parameters on MRR and SR. Finally, the cuckoo optimization algorithm (COA) was used for selection solutions in which the process reaches maximum material removal rate and minimum surface roughness simultaneously. Results indicated that the ANFIS technique has superiority in modeling of MRR and SR with high prediction accuracy. Also, results obtained while applying of COA have been compared with those derived from confirmatory experiments which validate the applicability and suitability of the proposed techniques in enhancing the performance of ECM process.

关键词： electrochemical machining process (ECM) modeling adaptive neuro-fuzzy inference system (ANFIS) optimization cuckoo optimization algorithm (COA)

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基于GA-ANFIS在石灰矿技术经济系统中的参数优化研究与应用实践

杨仕教,戴剑勇,曾晟

《中国工程科学》 2005年第7卷第6期页码 61-65

摘要：

为掌握水泥原料矿山系统中的技术经济参数对矿石成本影响的关联规律性，首先运用自适应模糊神经网络对矿山技术经济系统建模，再用并行遗传算法对模型求解，得到了确保矿石成本最小的各项最优技术经济指标，为提高矿山生产管理与经济效益提供了重要的参考价值。

关键词：自适应模糊神经网络并行遗传算法技术经济参数

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falling weight deflectometer parameters using hybrid model of genetic algorithm and adaptive neuro-fuzzy inference

《结构与土木工程前沿（英文）》页码 812-826 doi: 10.1007/s11709-023-0940-7

摘要： A falling weight deflectometer is a testing device used in civil engineering to measure and evaluate the physical properties of pavements, such as the modulus of the subgrade reaction (Y1) and the elastic modulus of the slab (Y2), which are crucial for assessing the structural strength of pavements. In this study, we developed a novel hybrid artificial intelligence model, i.e., a genetic algorithm (GA)-optimized adaptive neuro-fuzzy inference system (ANFIS-GA), to predict Y1 and Y2 based on easily determined 13 parameters of rigid pavements. The performance of the novel ANFIS-GA model was compared to that of other benchmark models, namely logistic regression (LR) and radial basis function regression (RBFR) algorithms. These models were validated using standard statistical measures, namely, the coefficient of correlation (R), mean absolute error (MAE), and root mean square error (RMSE). The results indicated that the ANFIS-GA model was the best at predicting Y1 (R = 0.945) and Y2 (R = 0.887) compared to the LR and RBFR models. Therefore, the ANFIS-GA model can be used to accurately predict Y1 and Y2 based on easily measured parameters for the appropriate and rapid assessment of the quality and strength of pavements.

关键词： falling weight deflectometer modulus of subgrade reaction elastic modulus metaheuristic algorithms

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Standard model of knowledge representation

Wensheng YIN

《机械工程前沿（英文）》 2016年第11卷第3期页码 275-288 doi: 10.1007/s11465-016-0372-3

摘要：

Knowledge representation is the core of artificial intelligence research. Knowledge representation methods include predicate logic, semantic network, computer programming language, database, mathematical model, graphics language, natural language, etc. To establish the intrinsic link between various knowledge representation methods, a unified knowledge representation model is necessary. According to ontology, system theory, and control theory, a standard model of knowledge representation that reflects the change of the objective world is proposed. The model is composed of input, processing, and output. This knowledge representation method is not a contradiction to the traditional knowledge representation method. It can express knowledge in terms of multivariate and multidimensional. It can also express process knowledge, and at the same time, it has a strong ability to solve problems. In addition, the standard model of knowledge representation provides a way to solve problems of non-precision and inconsistent knowledge.

关键词： knowledge representation standard model ontology system theory control theory multidimensional representation

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基于本体论的工艺信息描述方法研究

李莉,郝永平,舒启林,张建富

《中国工程科学》 2003年第5卷第11期页码 75-78

摘要：

依据本体论的概念论述了零件信息和制造资源信息的描述方法，给出了它们本体的定义方式。描述了零件本体和特征本体的属性，分析了各本体间和本体属性间的关系。以开发的CAPP系统为例，阐述了此描述方法在实际应用中体现出的特点。

关键词： CAPP 本体论零件本体特征本体制造资源本体工艺资源本体

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Simulation of foamed concrete compressive strength prediction using adaptive neuro-fuzzy inference system

Ahmad SHARAFATI, H. NADERPOUR, Sinan Q. SALIH, E. ONYARI, Zaher Mundher YASEEN

《结构与土木工程前沿（英文）》 2021年第15卷第1期页码 61-79 doi: 10.1007/s11709-020-0684-6

摘要： Concrete compressive strength prediction is an essential process for material design and sustainability. This study investigates several novel hybrid adaptive neuro-fuzzy inference system (ANFIS) evolutionary models, i.e., ANFIS–particle swarm optimization (PSO), ANFIS–ant colony, ANFIS–differential evolution (DE), and ANFIS–genetic algorithm to predict the foamed concrete compressive strength. Several concrete properties, including cement content (C), oven dry density (O), water-to-binder ratio (W), and foamed volume (F) are used as input variables. A relevant data set is obtained from open-access published experimental investigations and used to build predictive models. The performance of the proposed predictive models is evaluated based on the mean performance (MP), which is the mean value of several statistical error indices. To optimize each predictive model and its input variables, univariate (C, O, W, and F), bivariate (C–O, C–W, C–F, O–W, O–F, and W–F), trivariate (C–O–W, C–W–F, O–W–F), and four-variate (C–O–W–F) combinations of input variables are constructed for each model. The results indicate that the best predictions obtained using the univariate, bivariate, trivariate, and four-variate models are ANFIS–DE– (O) (MP= 0.96), ANFIS–PSO– (C-O) (MP= 0.88), ANFIS–DE– (O–W–F) (MP= 0.94), and ANFIS–PSO– (C–O–W–F) (MP= 0.89), respectively. ANFIS–PSO– (C–O) yielded the best accurate prediction of compressive strength with an MP value of 0.96.

关键词： foamed concrete adaptive neuro fuzzy inference system nature-inspired algorithms prediction of compressive strength

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Predication of discharge coefficient of cylindrical weir-gate using adaptive neuro fuzzy inference systems

Abbas PARSAIE,Amir Hamzeh HAGHIABI,Mojtaba SANEIE,Hasan TORABI

《结构与土木工程前沿（英文）》 2017年第11卷第1期页码 111-122 doi: 10.1007/s11709-016-0354-x

摘要： Settlement of sediments behind weirs and accumulation of materials floating on water behind gates decreases the performance of these structures. Weir-gate is a combination of weir and gate structures which solves them Infirmities. Proposing a circular shape for crest of weirs to improve their performance, investigators have proposed cylindrical shape to improve the performance of weir-gate structure and call it cylindrical weir-gate. In this research, discharge coefficient of weir-gate was predicated using adaptive neuro fuzzy inference systems (ANFIS). To compare the performance of ANFIS with other types of soft computing techniques, multilayer perceptron neural network (MLP) was prepared as well. Results of MLP and ANFIS showed that both models have high ability for modeling and predicting discharge coefficient; however, ANFIS is a bit more accurate. The sensitivity analysis of MLP and ANFIS showed that Froude number of flow at upstream of weir and ratio of gate opening height to the diameter of weir are the most effective parameters on discharge coefficient.

关键词： weir-gate soft computing crest geometry circular crest weir cylindrical shape

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from supercritical extraction using artificial neural networks and an adaptive-network-based fuzzy inference

J. Sargolzaei, A. Hedayati Moghaddam

《化学科学与工程前沿（英文）》 2013年第7卷第3期页码 357-365 doi: 10.1007/s11705-013-1336-3

摘要： Various simulation tools were used to develop an effective intelligent system to predict the effects of temperature and pressure on an oil extraction yield. Pomegranate oil was extracted using a supercritical CO (SC-CO ) process. Several simulation systems including a back-propagation neural network (BPNN), a radial basis function neural network (RBFNN) and an adaptive-network-based fuzzy inference system (ANFIS) were tested and their results were compared to determine the best predictive model. The performance of these networks was evaluated using the coefficient of determination ( ) and the mean square error (MSE). The best correlation between the predicted and the experimental data was achieved using the BPNN method with an of 0.9948.

关键词： oil recovery artificial intelligence extraction neural networks supercritical extraction

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Home location inference from sparse and noisy data: models and applications

Tian-ran HU,Jie-bo LUO,Henry KAUTZ,Adam SADILEK

《信息与电子工程前沿（英文）》 2016年第17卷第5期页码 389-402 doi: 10.1631/FITEE.1500385

摘要： Accurate home location is increasingly important for urban computing. Existing methods either rely on continuous (and expensive) Global Positioning System (GPS) data or suffer from poor accuracy. In particular, the sparse and noisy nature of social media data poses serious challenges in pinpointing where people live at scale. We revisit this research topic and infer home location within 100 m×100 m squares at 70% accuracy for 76% and 71% of active users in New York City and the Bay Area, respectively. To the best of our knowledge, this is the first time home location has been detected at such a fine granularity using sparse and noisy data. Since people spend a large portion of their time at home, our model enables novel applications. As an example, we focus on modeling people’s health at scale by linking their home locations with publicly available statistics, such as education disparity. Results in multiple geographic regions demonstrate both the effectiveness and added value of our home localization method and reveal insights that eluded earlier studies. In addition, we are able to discover the real buzz in the communities where people live.

关键词： Home location Mobility patterns Healthcare

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因果推理 Review

况琨, 李廉, 耿直, 徐雷, 张坤, 廖备水, 黄华新, 丁鹏, 苗旺, 蒋智超

《工程（英文）》 2020年第6卷第3期页码 253-263 doi: 10.1016/j.eng.2019.08.016

摘要：

因果推理是解释性分析的强大建模工具，它可使当前的机器学习变得可解释。如何将因果推理与机器学习相结合，开发可解释人工智能（XAI）算法，是迈向人工智能2.0的关键步骤之一。为了将因果推理的知识带给机器学习和人工智能领域的学者，我们邀请从事因果推理的研究人员，从因果推理的不同方面撰写了本综述。本综述包括以下几个部分：况琨博士的“平均因果效应评估——简要回顾与展望”，李廉教授的“反事实推理的归因问题”，耿直教授的“Yule-Simpson悖论和替代指标悖论”，徐雷教授的“因果发现CPT方法”，张坤教授的“从观测数据中发现因果关系”，廖备水和黄华新教授的“形式论辩在因果推理和解释中的作用”，丁鹏教授的“复杂实验中的因果推断”，苗旺教授的“观察性研究中的工具变量和阴性对照方法”，蒋智超博士的“有干扰下的因果推断”。

关键词：因果推断指示变量阴性对照因果推理和解释因果发现反事实推理治疗效果评价

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Engineering and Philosophy of Engineering

Rui-yu Yin,Bo-cong Li

《工程管理前沿（英文）》 2014年第1卷第2期页码 140-146 doi: 10.15302/J-FEM-2014021

摘要： Philosophy of engineering lays the philosophical foundation of recognition, understanding and management of engineering. Being the kernel of philosophy of engineering, engineering ontology becomes the master key to understanding of engineering. The paper proposes and interprets the principal theses of engineering ontology, which differs from understanding of engineering in separate elements. Engineering ontology believes that engineering is the direct, realistic productivity that runs dynamically and feasibly and creates values. Engineering involves the relationship between human beings and the nature as well as the relationship between human beings and the society, and it has been a basic motive force and a basic way of promoting the social development, so that engineering gains the ontological status and fundamental value in social existence and social development. From the historical point of view, the engineering appears before the emergence of technology and science. Engineering has its own basis for existence, its own structure and its own laws for movement and evolution. Engineering should not be simply regarded as the ramification and derivative from science or technology. Engineering ontology is the theoretical basis of the triism of “science, technology, and engineering”. To understand and handle the mutual relationship among engineering, technology and science, by the evaluation criteria of engineering as the direct productivity, the process and effect of engineering-centered selection, integration and construction must be emphasized and the characteristic and mechanism of selection, integration and construction must be paid high attention. Under no circumstance may the engineering be deemed as an unchanged matter, which is constantly evolving and developing, so the studies on engineering ontology are closely and internally related with the theory of engineering evolution.

关键词： engineering philosophy of engineering engineering ontology productivity engineering value

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连续生产线设备故障诊断专家系统的动态模糊推理机制的研究

谈理,刘谨,梅丽婷

《中国工程科学》 2005年第7卷第6期页码 57-60

摘要：

针对连续生产线设备故障诊断专家系统的研制，阐述了在建立模糊推理机过程中引入具有实时性的动态模糊关系的思想，并构造一个随无故障时间变化的动态隶属度函数来实现。

关键词：故障诊断专家系统模糊推理

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基于自适应网络模糊推理系统的移动机器人导航控制器 Research Article

Panati SUBBASH, Kil To CHONG

《信息与电子工程前沿（英文）》 2019年第20卷第2期页码 141-151 doi: 10.1631/FITEE.1700206

摘要：在障碍物高度杂乱的未知环境中自主导航是移动机器人研究的一个基本问题。提出一种基于自适应网络模糊推理系统（ANFIS）的差分驱动移动机器人导航控制器，用超声波传感器捕捉移动机器人周围的环境信息。设计了一个基于模糊逻辑的导航控制器，用于获取数据集训练ANFIS控制器。在移动机器人导航过程中，考虑到环境噪声对传感器读数的影响，将加性高斯白噪声添加到传感器读数中并反馈给已训练的ANFIS控制器。在3种不同环境下对移动机器人进行导航，评价该导航控制器的鲁棒性。通过与已有移动机器人导航控制器（如神经网络、模糊逻辑）比较行程长度、行程效率、弯曲能量，验证ANFIS控制器性能。仿真结果表明，与其他控制器相比，ANFIS控制器具有更好性能，能够在不同环境中顺利导航且不与障碍物发生碰撞。

关键词：自适应网络模糊推理系统；加性高斯白噪声；自主导航；移动机器人

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Ontological reconstruction of the clinical terminology of traditional Chinese medicine

null

《医学前沿（英文）》 2014年第8卷第3期页码 358-361 doi: 10.1007/s11684-014-0348-9

摘要：

This study proposes the ontological reconstruction of the current clinical terminology of traditional Chinese medicine (TCM). It also provides an overview of preliminary work related to the said reconstruction, including the ontology-based analysis of TCM clinical terminology. We conclude that the ontological reconstruction of TCM clinical terminology provides a proper translation from the idealized organizational model to real-world implementation and to a formalized, shared, and knowledge-based framework.

关键词： ontology traditional Chinese medicine clinical terminology

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一种新的融合本体和主机信息的改进禁忌搜索算法的主题爬虫方法 Research Article

刘景发1,王震1,2,钟国1,杨志和1

《信息与电子工程前沿（英文）》 2023年第24卷第6期页码 859-875 doi: 10.1631/FITEE.2200315

摘要：为解决传统主题爬虫方法存在的主题描述不完整和重复爬取已访问链接的问题，本文提出一种新的融合本体和主机信息的改进禁忌搜索算法的主题爬虫方法（FCITS_OH）。该方法基于形式概念分析（FCA）构建领域本体，在语义和知识层面描述主题。为避免重复爬取已访问的链接和扩大搜索范围，提出一种改进的禁忌搜索（ITS）算法和记忆主机信息的策略。此外，为改进未访问链接的主题相关性的评估方法，提出一种基于Web文本和链接结构的综合优先度评估方法。以旅游和暴雨灾害为主题的实验结果表明，对于不同的性能指标，所提出的爬虫方法优于文献中其它主题爬虫策略。

关键词：主题爬虫；禁忌搜索算法；本体；主机信息；优先度评估

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标题作者时间类型操作

Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing

Reza TEIMOURI, Hamed SOHRABPOOR

期刊论文

基于GA-ANFIS在石灰矿技术经济系统中的参数优化研究与应用实践

杨仕教,戴剑勇,曾晟

期刊论文

falling weight deflectometer parameters using hybrid model of genetic algorithm and adaptive neuro-fuzzy inference

期刊论文

Standard model of knowledge representation