Neural Network Simulation Of Nitrogen Transformation Cycle

Kmeť, Tibor

doi:10.7148/2009-0352-0358

Cited by 3 publications

(6 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The multi-layered feed forward network shown in Fig. Further discussion and detail explanation of this adaptive critic methods for optimal control problem with control and state constraints, fixed terminal time and free terminal condition can be found in [3], [4], [6]. The adaptive critic neural network shown in Fig.…”

Section: Neural Network Solution Of Optimal Control Problemmentioning

confidence: 99%

“…We will investigate two strategies [4], [5]: 1)instantaneous maximal biomass production as a goal function (local optimality), i.e.,ẋ 6 = f 6 (x, u) → max for all t, under the constraint u ∈ [u min , u max ]. We are interested in the ability of Cladocera to adapt both the filtration area and filter density to the amount and size structure of the food particles (algae) population.…”

Section: Model Of Feeding Adaptation and Neural Network Simulationmentioning

confidence: 99%

“…There has been a growing number of applications reported in the literature that employ neural networks to optimal control of nonlinear processes which is one of the most active subjects in control theory. In the recent years, the multi-layer feedforward neural networks have been used for obtaining numerical solutions to the optimal control problem [4], [6], [9]. Most of the literature that deals with numerical methods for the solution of general optimal control problems focuses on the algorithms for solving discretized problems.…”

Section: Introductionmentioning

confidence: 99%

“…There is rarely an analytical solution although several numerical computation approaches have been proposed (for example see [2], [7]) for solving a optimal control problem. In the present paper we extend adaptive critic neural network architecture proposed by [4] to the optimal control problems with open final time using recurrent neural network. In the recent years, the multi-layer feedforward neural networks have been used for obtaining numerical solutions to the optimal control problem [4], [6], [9].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimal Control Problem of Feeding Adaptations of Daphnia and Neural Network Simulation

Kmeť¹,

Kmet’ov²

2010

AIP Conference Proceedings

View full text Add to dashboard Cite

A neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints and open final time. The optimal control problem is transcribed into nonlinear programming problem, which is implemented with adaptive critic neural network [9] and recurrent neural network for solving nonlinear proprojection equations [10]. The proposed simulation methods is illustrated by the optimal control problem of feeding adaptation of filter feeders of Daphnia. Results show that adaptive critic based systematic approach and neural network solving of nonlinear equations hold promise for obtaining the optimal control with control and state constraints and open final time.Keywords: optimal control problem with control and state constraints, open final time, adaptive critic neural network synthesis, recurrent neural network, numerical solution and example PACS: 49K15, 49M25, 49M37, 49M05, 92D25, 68T05

show abstract

Section: Neural Network Solution Of Optimal Control Problemmentioning

confidence: 99%

Section: Model Of Feeding Adaptation and Neural Network Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal Control Problem of Feeding Adaptations of Daphnia and Neural Network Simulation

Kmeť¹,

Kmet’ov²

2010

AIP Conference Proceedings

View full text Add to dashboard Cite

show abstract

“…The proposed adaptive critic neural network is able to meet the convergence tolerance values chosen by us, which leads to satisfactory simulation results. For detail explanation of adaptive critic neural network see (Kmet, 2009), (Padhi et al, 2006) and (Padhi et al, 2001). To solve equations (7) we are concerned the following nonlinear projection equation (for detail description see (Xia et al, 2007)):…”

Section: Neural Network Solution Of Optimal Control Problemmentioning

confidence: 99%

Modelling And Simulation Of Filter Adaptation By Daphnia

Kmeť¹,

Kmetova²

2011

ECMS 2011 Proceedings Edited By: T. Burczynski, J. Kolodziej, A. Byrski, M. Carvalho

Self Cite

View full text Add to dashboard Cite

KEYWORDSmathematical model of ecosystem, stability analysis, feeding adaptation of Daphnia, optimal control problem, adaptive critic and recurrent neural network, numerical simulation ABSTRACT A model of feeding adaptation of a filter feeder in the framework of a pelagic ecosystem is constructed by modifying the simplified ecosystem model AQUAMOD for the presence of several different sized species of algae. Stability analysis of equilibria and some numerical simulation is given. It is shown that Hopf bifurcation may occur depending on filtration rate. Also the assumption that filtration adaptability represents optimization type process is incorporated. Two possible strategies were followed: an instantaneous optimality at each time interval and an integral formulation, maximization of the integral biomass. The optimal control problem is transcribed into nonlinear programming problem, which is implemented with adaptive critic neural network and recurrent neural network for solving nonlinear projection equations. Results show that adaptive critic based systematic approach and neural network solving of nonlinear equations hold promise for obtaining the optimal control with control and state constraints. MODEL DESCRIPTIONIn this paper we consider a simplified ecosystem model AQUAMOD for the presence of several different sized species of algae. The model consists of phosphorus (x 1 ) as a limiting nutrient for growth of four species of different sized algae (x 2 − x 5 ) and zooplankton (x 6 ). Similar models of n species of microorganisms competing exploitatively for one, two or more growth-limiting nutrients are used to study continuous culture of microorganisms in chemostat under constant condition (Smith et al., 1995) without any predators. The model is described by the following system of ordinary differential equation (1)

show abstract

The Pattern of Change in Depressive Symptoms and Inflammatory Markers After Electroconvulsive Therapy

Desfossés

Peredo

Chabot

et al. 2021

J ECT

View full text Add to dashboard Cite

Depression is a major mental health disorder, and its pathophysiology is still largely unknown, as is the action mechanism of electroconvulsive therapy (ECT). Some evidence suggests that inflammation might play a role in depression, and several studies have attempted to demonstrate a link between ECT and cytokines. This systematic review used a qualitative analysis to assess the effect of ECT on inflammatory markers as it relates to the clinical response of depressive symptoms in major depressive disorders. The bibliographic search engines CINAHL, Embase, PsychInfo, and PubMed were used to identify articles published up to July 2020. Search terms related to depression, ECT, and inflammation were used. Descriptive statistical analyses were performed to relate changes in inflammatory markers to clinical response to ECT. Twenty-five studies were included in the analysis. No systematic increases or decreases were found in a given inflammatory marker over the ECT; however, we observed that tumor necrosis factor α and interleukin-6 (IL-6) were more often found to be decreased after ECT, whereas IL-8 and IL-10 were more often found to be increased after treatment. No trend in correlation was found between the degree of clinical improvement of depressive symptoms and the variation of any inflammatory markers, despite positive clinical response to ECT. Great heterogeneity with regard to methodology used and lack of power of the studies included in this review could explain the lack of systematic change and correlation found in this study. Future research conducted on this subject should take into account these methodological limitations to allow subsequent meta-analysis.

show abstract

Neural Network Simulation Of Nitrogen Transformation Cycle

Cited by 3 publications

References 13 publications

Optimal Control Problem of Feeding Adaptations of Daphnia and Neural Network Simulation

Optimal Control Problem of Feeding Adaptations of Daphnia and Neural Network Simulation

Modelling And Simulation Of Filter Adaptation By Daphnia

The Pattern of Change in Depressive Symptoms and Inflammatory Markers After Electroconvulsive Therapy

Contact Info

Product

Resources

About