Adaptive Neuro-Fuzzy Inference System (ANFIS) and Radial Basis Function Neural Network (RBF NN) have been developed for prediction of solubility of various gases in polystyrene. Solubility of butane, isobutene, carbon dioxide, 1,1,1,2-tetrafluoroethane (HFC-134a), 1-chloro-1,1-difluoroethane (HCFC-142b), 1,1-difluoroethane (HFC-l52a) and nitrogen in polystyrene is modeled by ANFIS and RBF NN in a wide range of pressure and temperature with high accuracy. The results obtained in this work indicate that ANFIS and RBF NN are effective methods for prediction of solubility of gases in polystyrene and have better accuracy and simplicity compared with the classical methods.

Prediction of solubility of gases in polystyrene by Adaptive Neuro-Fuzzy Inference System and Radial Basis Function Neural Network

A new kind of vibration isolation and mitigation device with high damping is designed and fabricated for reducing dynamic responses of a platform under the excitation with wide frequency range. Tests are carried out to consider the influence of the frequency and amplitude of excitation on the properties of the device. The dynamic model of the platform incorporating with the vibration isolation and mitigation devices is established, and dynamic responses of the mitigated platform are calculated under different excitations. It can be shown from comparison between responses of the mitigated and unmitigated structures in time domain and frequency domain that the devices can significantly reduce dynamic responses of the platform.

Vibration suppression on a platform by using vibration isolation and mitigation devices

Seismic vibration control of offshore jacket platforms using decentralized sliding mode algorithm

Dynamic analysis and control application of vibration isolation system with magnetic suspension on satellites

Purpose – The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence, the purpose of this paper is to present a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research.Design/methodology/approach – The paper builds upon our previous survey of this field which was carried out for the ten‐year period 1995‐2004. Like the previous survey, it uses Elsevier's Science Direct database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus, the application categories adopted are: design; scheduling; process planning and control; and quality, maintena...

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C.H. Chou

Papers

Intelligent active vibration control in an isolation platform

Adaptive fuzzy neural network control on the acoustic field in a duct

Active control by using optical sensors on the acoustic radiation from square plates