共查询到10条相似文献,搜索用时 281 毫秒
1.
In this study, micellar-enhanced ultrafiltration (MEUF) was applied to remove zinc ions from wastewater efficiently. Frequently, experimental design and artificial neural networks (ANNs) have been successfully used in membrane filtration process in recent years. In the present work, prediction of the permeate flux and rejection of metal ions by MEUF was tested, using design of experiment (DOE) and ANN models. In order to reach the goal of determining all the influential factors and their mutual effect on the overall performance the fractional factorial design has been used. The results show that due to the complexity in generalization of the MEUF process by any mathematical model, the neural network proves to be a very promising method in compared with fractional factorial design for the purpose of process simulation. These mathematical models are found to be reliable and predictive tools with an excellent accuracy, because their AARE was ±0.229%, ±0.017%, in comparison with experimental values for permeate flux and rejection, respectively. 相似文献
2.
For fuzzy systems to be implemented effectively, the fuzzy membership function (MF) is essential. A fuzzy system (FS) that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output (SISO) FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s output. Utilizing a variety of non-linear techniques, a SISO FS is simulated. The results of FS experiments conducted in comparable conditions are then compared. The simulated results and the results of the experimental setup agree fairly well. The findings of the suggested model demonstrate that the relative error is abated to a sufficient range (≤ ± 10%) and that the mean absolute percentage error (MPAE) is reduced by around 66.2%. The proposed strategy to reduce MAPE using an FS improves the system’s performance and control accuracy. By using the best input and output MFs protocol, the energy and financial efficiency of every SISO FS can be improved with very little tuning of MFs. The proposed fuzzy system performed far better than other modern days approaches available in the literature. 相似文献
3.
为设计出符合消费者感性需求的产品,采用基于模糊逻辑的产品意象造型设计方法。首先确定感性词汇与造型设计要素,利用模糊逻辑建立二者之间的关系。通过模糊化、模糊规则的构建、模糊推理以及反模糊化等过程进行模糊逻辑控制器的设计,用Matlab建立仿真模型,最后通过测试验证了模型的有效性。结合折叠自行车造型设计进行研究,结果表明该方法是正确可行的。 相似文献
4.
Luciano Specht Oleg Khatchatourian 《International Journal of Pavement Engineering》2014,15(9):799-809
The viscosity of binder is of great importance during the handling, mixing, application and compaction of asphalt in highway surfacing. This paper presents experimental data and the application of artificial intelligence techniques (statistics, artificial neural networks (ANNs) and fuzzy logic) to modelling of apparent viscosity in asphalt–rubber binders. The binders were prepared in the laboratory by varying the rubber content (RC), rubber particle size, duration and temperature of mixture in conformity with a statistical design plan. Multi-factorial analysis of variance showed that the RC has a major influence on the viscosity observed for the considered interval of parameters variation. When only limited experimental data of design matrix are available for modelling, the fuzzy logic model is the best model to be used. In addition, the combined use of ANN and multiple regression analysis improved the characteristics of the neural network. 相似文献
5.
Deepak Sankar Somasundaram 《工程优选》2013,45(10):1043-1062
This article presents an approach to enhance the Hooke-Jeeves optimization algorithm through the use of fuzzy logic. The Hooke-Jeeves algorithm, similar to many other optimization algorithms, uses predetermined fixed parameters. These parameters do not depend on the objective function values in the current search region. In the proposed algorithm, several fuzzy logic controllers are integrated at the various stages of the algorithm to create a new optimization algorithm: Fuzzy-Controlled Hooke-Jeeves algorithm. The results of this work show that incorporating fuzzy logic in the Hooke-Jeeves algorithm can improve the ability of the algorithm to reach an extremum in different typical optimization test cases and design problems. Sensitivity analysis of the variables of the algorithm is also considered. 相似文献
6.
Safety assessment based on conventional tools (e.g. probability risk assessment (PRA)) may not be well suited for dealing with systems having a high level of uncertainty, particularly in the feasibility and concept design stages of a maritime or offshore system. By contrast, a safety model using fuzzy logic approach employing fuzzy IF–THEN rules can model the qualitative aspects of human knowledge and reasoning processes without employing precise quantitative analyses. A fuzzy-logic-based approach may be more appropriately used to carry out risk analysis in the initial design stages. This provides a tool for working directly with the linguistic terms commonly used in carrying out safety assessment. This research focuses on the development and representation of linguistic variables to model risk levels subjectively. These variables are then quantified using fuzzy sets. In this paper, the development of a safety model using fuzzy logic approach for modelling various design variables for maritime and offshore safety based decision making in the concept design stage is presented. An example is used to illustrate the proposed approach. 相似文献
7.
Ayman A. Aly Mohamed O. Elhabib Bassem F. Felemban B. Saleh Dac-Nhuong Le 《计算机、材料和连续体(英文)》2022,72(1):93-107
The application of the guided missile seeker is to provide stability to the sensor's line of sight toward a target by isolating it from the missile motion and vibration. The main objective of this paper is not only to present the physical modeling of two axes gimbal system but also to improve its performance through using fuzzy logic controlling approach. The paper is started by deriving the mathematical model for gimbals motion using Newton's second law, followed by designing the mechanical parts of model using SOLIDWORKS and converted to xml file to connect dc motors and sensors using MATLAB/SimMechanics. Then, a Mamdani-type fuzzy and a Proportional-Integral-Derivative (PID) controllers were designed using MATLAB software. The performance of both controllers was evaluated and tested for different types of input shapes. The simulation results showed that self-tuning fuzzy controller provides better performance, since no overshoot, small steady-state error and small settling time compared to PID controller. 相似文献
8.
In the changing business environment, manufacturing firms can survive by catering to the dynamic demands of the modern customers. Lean principles imply zero inventory and agile principles necessitate safety inventory to tackle volatile market conditions. The leagile paradigm is gaining importance in the contemporary scenario which includes both lean and agile principles. This article presents the conceptual model of leagility imbibed with lean and agile principles. A fuzzy logic approach has been used for the evaluation of leagility in supply chains. This article is used to compute the performance of supply chains using both lean and agile concepts as leagility supply chains using a fuzzy logic approach. 相似文献
9.
In this work, the dynamic model, flux-current-rotor position and torque-current-rotor position values of the switched reluctance
motor (SRM) are obtained in MATLAB/Simulink. Motor control speed is achieved by self-tuning fuzzy PI (Proportional Integral)
controller with artificial neural network tuning (NSTFPI). Performance of NSTFPI controller is compared with performance of
fuzzy logic (FL) and fuzzy logic PI (FLPI) controllers in respect of rise time, settling time, overshoot and steady state
error. 相似文献
10.
Quantifying uncertainty during risk analysis has become an important part of effective decision-making and health risk assessment. However, most risk assessment studies struggle with uncertainty analysis and yet uncertainty with respect to model parameter values is of primary importance. Capturing uncertainty in risk assessment is vital in order to perform a sound risk analysis. In this paper, an approach to uncertainty analysis based on the fuzzy set theory and the Monte Carlo simulation is proposed. The question then arises as to how these two modes of representation of uncertainty can be combined for the purpose of estimating risk. The proposed method is applied to a propylene oxide polymerisation reactor. It takes into account both stochastic and epistemic uncertainties in the risk calculation. This study explores areas where random and fuzzy logic models may be applied to improve risk assessment in industrial plants with a dynamic system (change over time). It discusses the methodology and the process involved when using random and fuzzy logic systems for risk management. 相似文献