An adaptive neuro-fuzzy model for the prediction and control of light in integrated lighting schemes

2005 ◽  
Vol 37 (4) ◽  
pp. 343-351 ◽  
Author(s):  
CP Kurian ◽  
S Kuriachan ◽  
J Bhat ◽  
RS Aithal
Keyword(s):  
Fuzzy Model ◽  
Neuro Fuzzy ◽  
Prediction And Control ◽  
And Control

scholarly journals Advanced Construction of the Dynamic Matrix in Numerically Efficient Fuzzy MPC Algorithms

Algorithms ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 25
Author(s):  
Piotr M. Marusak
Keyword(s):  
Process Model ◽  
Linear Models ◽  
Control Plant ◽  
Fuzzy Model ◽  
Nonlinear Process ◽  
Linear Constraints ◽  
Good Prediction ◽  
Dynamic Matrix ◽  
Prediction And Control ◽  
And Control

A method for the advanced construction of the dynamic matrix for Model Predictive Control (MPC) algorithms with linearization is proposed in the paper. It extends numerically efficient fuzzy algorithms utilizing skillful linearization. The algorithms combine the control performance offered by the MPC algorithms with nonlinear optimization (NMPC algorithms) with the numerical efficiency of the MPC algorithms based on linear models in which the optimization problem is a standard, easy-to-solve, quadratic programming problem with linear constraints. In the researched algorithms, the free response obtained using a nonlinear process model and the future trajectory of the control signals is used to construct an advanced dynamic matrix utilizing the easy-to-obtain fuzzy model. This leads to obtaining very good prediction and control quality very close to those offered by NMPC algorithms. The proposed approach is tested in the control system of a nonlinear chemical control plant—a CSTR reactor with the van de Vusse reaction.

scholarly journals NEURO-FUZZY MODELLING IN ANAEROBIC WASTEWATER TREATMENT FOR PREDICTION AND CONTROL

2014 ◽  
pp. 51-56
Author(s):  
Snejana Yordanova ◽  
Rusanka Petrova ◽  
Nelly Noykova ◽  
Plamen Tzvetkov
Keyword(s):  
Wastewater Treatment ◽  
Prediction Models ◽  
Biogas Production ◽  
Organic Load ◽  
Model Parameters ◽  
Box Models ◽  
Neuro Fuzzy ◽  
Prediction And Control ◽  
And Control

The aim of the present paper is to develop neuro-fuzzy prediction models in MATLAB environment of the anaerobic organic digestion process in wastewater treatment from laboratory and simulated experiments accounting for the variable organic load, ambient influence and microorganisms state. The main contributions are determination of significant model parameters via graphical sensitivity analysis, simulation experimentation, design and study of two “black-box” models for the biogas production rate, based on classical feedforward backpropagation and Sugeno fuzzy logic neural networks respectively. The models application is demonstrated in process predictive control

An insight into Case Management and Challenges in Veteran Suicide Prevention

2020 ◽  
pp. 14-25
Author(s):  
Tamara Green
Keyword(s):  
Case Management ◽  
Suicide Prevention ◽  
Suicide Risk ◽  
Digital Transformation ◽  
Prevention Science ◽  
Historical Records ◽  
Military Members ◽  
Prediction And Control ◽  
And Control ◽  
Insight Into

Much of the literature, policies, programs, and investment has been made on mental health, case management, and suicide prevention of veterans. The Australian “veteran community is facing a suicide epidemic for the reasons that are extremely complex and beyond the scope of those currently dealing with them.” (Menz, D: 2019). Only limited work has considered the digital transformation of loosely and manual-based historical records and no enablement of Artificial Intelligence (A.I) and machine learning to suicide risk prediction and control for serving military members and veterans to date. This paper presents issues and challenges in suicide prevention and management of veterans, from the standing of policymakers to stakeholders, campaigners of veteran suicide prevention, science and big data, and an opportunity for the digital transformation of case management.

NEURO-FUZZY MODEL FOR ENVIRONMENTAL IMPACT ASSESSMENT

2011 ◽  
Vol 10 (3) ◽  
pp. 381-386 ◽  
Author(s):  
Alexandru Trandabat ◽  
Marius Pislaru ◽  
Silvia Avasilcai
Keyword(s):  
Environmental Impact ◽  
Impact Assessment ◽  
Environmental Impact Assessment ◽  
Fuzzy Model ◽  
Neuro Fuzzy
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