共查询到20条相似文献，搜索用时 0 毫秒
1.
Elif Derya Übeyli 《Expert Systems》2010,27(4):259-266
Abstract: A new approach based on an adaptive neuro‐fuzzy inference system (ANFIS) is presented for diagnosis of diabetes diseases. The Pima Indians diabetes data set contains records of patients with known diagnosis. The ANFIS classifiers learn how to differentiate a new case in the domain by being given a training set of such records. The ANFIS classifier is used to detect diabetes diseases when eight features defining diabetes indications are used as inputs. The proposed ANFIS model combines neural network adaptive capabilities and the fuzzy logic qualitative approach. The conclusions concerning the impacts of features on the diagnosis of diabetes disease are obtained through analysis of the ANFIS. The performance of the ANFIS model is evaluated in terms of training performances and classification accuracies and the results confirm that the proposed ANFIS model has potential in detecting diabetes diseases. 相似文献
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A method based on multiple adaptive‐network‐based fuzzy inference system (MANFIS) is presented for the synthesis of electrically thin and thick rectangular microstrip antennas (MSAs). MANFIS is an extension of a single‐output adaptive‐network‐based fuzzy inference system to produce multiple outputs. Six optimization algorithms, least‐squares, nelder‐mead, genetic, hybrid learning, differential evolution and particle swarm, are used to identify the parameters of MANFIS. The synthesis results of MANFIS are in very good agreement with the experimental results available in the literature. When the performances of MANFIS models are compared with each other, the best result is obtained from the MANFIS model optimized by the least‐squares algorithm. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008. 相似文献
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Cutting tool wear estimation for turning 总被引：1，自引：0，他引：1
Vishal S. Sharma S. K. Sharma Ajay K. Sharma 《Journal of Intelligent Manufacturing》2008,19(1):99-108
The experimental investigation on cutting tool wear and a model for tool wear estimation is reported in this paper. The changes
in the values of cutting forces, vibrations and acoustic emissions with cutting tool wear are recoded and analyzed. On the
basis of experimental results a model is developed for tool wear estimation in turning operations using Adaptive Neuro fuzzy
Inference system (ANFIS). Acoustic emission (Ring down count), vibrations (acceleration) and cutting forces along with time
have been used to formulate model. This model is capable of estimating the wear rate of the cutting tool. The wear estimation
results obtained by the model are compared with the practical results and are presented. The model performed quite satisfactory
results with the actual and predicted tool wear values. The model can also be used for estimating tool wear on-line but the
accuracy of the model depends upon the proper training and section of data points. 相似文献
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S.M.R. Kazemi Mir Meisam Seied Hoseini S. Abbasian‐Naghneh Seyed Habib A. Rahmati 《International Transactions in Operational Research》2014,21(2):311-326
The continuing growth in size and complexity of electric power systems requires the development of applicable load forecasting models to estimate the future electrical energy demands accurately. This paper presents a novel load forecasting approach called genetic‐based adaptive neuro‐fuzzy inference system (GBANFIS) to construct short‐term load forecasting expert systems and controllers. At the first stage, all records of data are searched by a novel genetic algorithm (GA) to find the most suitable feature of inputs to construct the model. Then, determined inputs are fed into the adaptive neuro‐fuzzy inference system to evolve the initial knowledge‐base of the expert system. Finally, the initial knowledge‐base is searched by another robust GA to induce a better cooperation among the rules by rule weight derivation and rule selection mechanisms. We show the superiority and applicability of our approach by applying it to the Iranian monthly electrical energy demand problem and comparing it with the most frequently adopted approaches in this field. Results indicate that GBANFIS outperforms its rival approaches and is a promising tool for dealing with short‐term load forecasting problems. 相似文献
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知识表示是专家系统求解能力及正确性的基础。针对不同知识表示方法的局限性,采用框架与产生式知识表示法结合表示专家知识。同时鉴于传统知识表示及推理方法在描述事实生产中不确定知识及经验中的缺陷问题,将模糊推理与知识表示相结合,应用模糊因子,定量细化描述模糊知识;并结合知识表示特点应用动态加权平均匹配函数及模糊推理方法,提出基于模糊框架-产生式知识表示方法及推理的研究,量化地表示知识及推理过程,为决策人员提供更加直观、准确的推理依据。 相似文献
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基于Visual Basic 6.0的故障智能诊断系统设计方法的研究 总被引：4，自引：0，他引：4
采用面向对象方法和 ＶＢ６．０程序设计语言,开发了一个故障智能诊断平台系统,该系统可针对不同对象建立诊断任务和环境。文章首先介绍了该系统的结构和各模块的功能,然后阐述了系统知识库建立的方法和推理机制。系统采用模糊推理与规则推理相结合的方法,具有较高的准确性。最后给出了一个系统的诊断实例。 相似文献
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基于模糊推理和自学习的工程机械故障诊断专家系统 总被引：5，自引：0，他引：5
以LTU90A摊铺机为研究切入点,针对其工作特点和智能化故障诊断需求,以故障诊断的理论和方法为基础,综合运用模糊推理、数据库、人工智能、专家系统等理论,研究并开发了基于知识库的摊铺机故障诊断专家系统。该系统实现了摊铺机的智能诊断以及诊断知识库的自学习,较大地提高了摊铺机故障诊断系统的准确性以及可扩展性。该研究成果已经得到实际应用,并已开始推广到路面施工机群的其他大型机械上。 相似文献
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Hadi Chahkandi Nejad Mohsen Farshad Fereidoun Nowshiravan Rahatabad Omid Khayat 《Expert Systems》2016,33(1):70-76
In this paper, a gradient‐based back propagation dynamical iterative learning algorithm is proposed for structure optimization and parameter tuning of the neuro‐fuzzy system. Premise and consequent parameters of the neuro‐fuzzy model are initialized randomly and then tuned by the proposed iterative algorithm. The learning algorithm is based on the first order partial derivative of the output with respect to the structure parameters. The first order derivative of the model output with respect to the structure parameters determines the sensitivity of the model to structure parameters. The sensitivity values are then used to set the tuning factors and parameters updating step sizes. Therefore, an adaptive dynamical iterative scheme is achieved which adapts the learning procedure to the current state of the performance during the optimization process. Larger tuning step sizes make the convergence speed higher and vice versa. In this regard, this parameter is treated according to the calculated sensitivity of the model to the parameter. The proposed learning algorithm is compared with the least square back propagation method, genetic algorithm and chaotic genetic algorithm in the neuro‐fuzzy model structure optimization. Smaller mean square error and shorter learning time are sought in this paper, and the performance of the proposed learning algorithm is versified regarding these criteria. 相似文献
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基于模糊推理的网络故障诊断研究 总被引：1，自引：0，他引：1
设计了一个可用于网络故障诊断的基于模糊推理的专家系统模型。为了验证此模型的有效性,设计和实现了一个原型系统。该系统的测试结果显示,故障诊断和定位的准确性较高,可以满足校园网的故障诊断和维护的需要。 相似文献
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Anita Thakur Prakriti Aggarwal Ashwani Kumar Dubey Ahmed Abdelgawad Alvaro Rocha 《Expert Systems》2023,40(1):e13119
Agriculture Industry is highly dependent on environmental and weather conditions. Many times, crops are spoiled because of sudden changes in weather. Therefore, we need a decision model to take care the water requirement of sensitive crops of agriculture industry. The proposed work presents a novel and proficient hybrid model for sensitive crop irrigation system (SCIS). For implementation of the model, brassica crop is taken. The duration and amount of water to be supplied is based upon the weather prediction and soil condition information. The decision model is developed using adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) for brassica crops. In this model, if the input data values are available in range, then ANFIS model would be preferred and if the data sets are available for training, testing and validation then ANN model would be the best choice. The soil moisture, soil status in terms of temperature and leaf wetness are the input and flow control of sprinklers is the out for SCIS. The predicted outputs are analysed to assert the suitability of the proposed approach in the brassica crops. The proposed SCIS achieved an accuracy of 91% and 99% for ANFIS and ANN models respectively. 相似文献
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基于规则的专家系统中不确定性推理的研究 总被引：17，自引：1，他引：17
提出了权值法和修正权值法两种不确定性推理算法,与常用的几种方法相比,权值法根据各证据重要程度的不同,区别对待证据的可信度信息,同时充分利用每一条信息;修正权值法除了具有权值法的优点外,又区分了可信度分布的差异。运用修正权值法已成功建造了多个实用专家系统。 相似文献
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一种模糊矩阵并行推理算法及其应用 总被引：1，自引：0，他引：1
针对高炉专家系统知识库和推理机的特点，采用模糊集理论中的隶属函数的方法实现了知识的模糊矩阵表示和推理，提出了一种基于模糊矩阵的并行推理算法，提高了高炉专家系统的推理效率 相似文献
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文章提出了一个基于模糊逻辑的关键工程项目风险管理的专家系统,包括项目风险的评价排序、风险措施的成本估算、风险措施的优化选择等三个主功能模块。通过该系统,项目管理人员可以清楚了解工程项目风险的大小、重要性和合理选择科学的风险管理措施。 相似文献
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针对风险评估过程中存在专家权重难以合理设置,评估结果受专家主观性影响大等问题,提出一种基于自适应专家权重的信息系统风险评估模型SAEW-ISRA,给出一种细粒度专家权重自适应调整方法.首先,在评估过程中引入三角模糊数对风险指标属性评分;其次,根据专家评分模糊度描述专家知识量,结合与专家群体评分的距离构建后验权重,可使专... 相似文献
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段荣华 《计算机测量与控制》2019,27(1):85-91
松散回潮属于大时滞系统,其出口烟叶水分控制所采用的带前馈-串级控制达不到理想的控制效果。在生产过程中需要根据经验手动修改加水系数,并没有真正实现完全自动化控制。提出了一种将专家系统、模糊推理和常规PID控制相互结合的新方法实现了松散回朝出口水分的控制,利用专家系统对加水系数进行自动决策;采用模糊推理方法分别对前室加水控制器与后室水分控制器的PID参数进行了在线自适应整定,实现了松散回潮出口水分控制的全自动化,提高了松散回潮出口水分的稳定性与精确性。 相似文献
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The operational levels of production management, often called production activity control (PAC) or manufacturing process control, require increasing reaction capabilities in order to adapt the workshop management to the changes of its environment. It often implies giving more responsibilities to the low decision levels. However, the management of the corresponding degrees of freedom is generally unusual. In such a situation, decision support systems (DSSs) provide a way to reconcile the satisfaction of mid-level objectives and the reaction requirements. A conceptual model is described that provides a design framework for a PAC DSS. Since the available knowledge lies mainly in expertise, a DSS has been implemented using a knowledge-based system. The uncertainty and imprecision of the managed information led to the use of fuzzy logic as a modeling tool. Moreover, various inference semantics have been implemented in the expert rules because different kinds of reasoning have been identified. Two versions of the DSS are described and several examples of implemented reasoning processes are developed. 相似文献
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Mal–rey Lee 《Expert Systems》2002,19(4):201-207
Huge and complex systems such as nuclear power generating stations are likely to cause the operators to make operational mistakes for a variety of inexplicable reasons and to produce ambiguous and complicated symptoms in the case of an emergency. Therefore, a safety protection system to assist the operators in making proper decisions within a limited time is required. In this paper, we develop a reliable and improved diagnosis system using the fuzzy inference method so that the system can classify accident symptoms and identify the most probable causes of accidents in order for appropriate actions to be taken to mitigate the consequences. In the computer simulation, the proposed system proved to be able to classify accident types within only 20–30 s. Therefore, the corresponding operation guidelines can be determined in a very short time to put the nuclear power plant in a safe state immediately after the accident. 相似文献
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The application of conjunctive aggregation functions in fuzzy control systems with n inputs is discussed, and the effect of the choice of a continuous t‐norm in the inference phase for Takagi–Sugeno–Kang (TSK) systems is computed. A continuous t‐norm modeling AND connective in antecedent part of fuzzy rules can be reduced just to strict or nilpotent t‐norm. The isomorphism of strict (nilpotent) t‐norms enables simpler fitting of TSK fuzzy system parameters and reduces the computational complexity. Similar principle can also be used in the case of some noncommutative conjunctive aggregation functions modeling AND connective. The effect of the choice of a continuous t‐norm is then evaluated on well‐known case studies in fuzzy control, the Sinc function, and the urban traffic noise control system. 相似文献