scholarly journals Modelling Complexity and Uncertainty in Fisheries Stock Assessment

2021 ◽  
Author(s):  
◽  
D'Arcy Webber
Keyword(s):  
New Zealand ◽  
State Space ◽  
Ross Sea ◽  
Stock Assessment ◽  
State Space Model ◽  
Computational Cost ◽  
Original Model ◽  
Agent Based Models ◽  
Agent Based ◽  
Space Model

<p>Stock assessment models are used to determine the population size of fish stocks. Although stock assessment models are complex, they still make simplifying assumptions. Generally, they treat each species separately, include little, if any, spatial structure, and may not adequately quantify uncertainty. These assumptions can introduce bias and can lead to incorrect inferences. This thesis is about more realistic models and their inference. This realism may be incorporated by explicitly modelling complex processes, or by admitting our uncertainty and modelling it correctly.  We develop an agent-based model that can describe fish populations as a collection of individuals which differ in their growth, maturation, migration, and mortality. The aim of this model is to better capture the richness in natural processes that determine fish abundance and subsequent population response to anthropogenic removals. However, this detail comes at considerable computational cost. A single model run can take many hours, making inference using standard methods impractical. We apply this model to New Zealand snapper (Pagurus auratus) in northern New Zealand.  Next, we developed an age-structured state-space model. We suggest that this sophisticated model has the potential to better represent uncertainty in stock assessment. However, it pushes the boundaries of the current practical limits of computing and we admit that its practical application remains limited until the MCMC mixing issues that we encountered can be resolved.   The processes that underpin agent-based models are complex and we may need to seek new sources of data to inform these types of models. To make a start here we derive a state-space model to estimate the path taken by individual fish from the day they are tagged to the day of their recapture. The model uses environmental information collected using pop-up satellite archival tags. We use tag recorded depth and oceanographic temperature to estimate the location at any given time. We apply this model to Antarctic toothfish (Dissostichus mawsoni) in the Ross Sea.  Finally, to reduce the computational burden of agent-based models we use Bayesian emulation. This approach replaces the simulation model with an approximating algorithm called an emulator. The emulator is calibrated using relatively few runs of the original model. A good emulator provides a close approximation to the original model and has significant speed gains. Thus, inferences become tractable.  We have made the first steps towards developing a tractable approach to fisheries modelling in complex settings through the creation of realistic models, and their emulation. With further development, Bayesian emulation could result in the increased ability to consider and evaluate innovative methods in fisheries modelling. Future avenues for application and exploration range from spatial and multi species models, to ecosystem-based models and beyond.</p>

scholarly journals Modelling Complexity and Uncertainty in Fisheries Stock Assessment

2021 ◽  
Author(s):  
◽  
D'Arcy Webber
Keyword(s):  
New Zealand ◽  
State Space ◽  
Ross Sea ◽  
Stock Assessment ◽  
State Space Model ◽  
Computational Cost ◽  
Original Model ◽  
Agent Based Models ◽  
Agent Based ◽  
Space Model

<p>Stock assessment models are used to determine the population size of fish stocks. Although stock assessment models are complex, they still make simplifying assumptions. Generally, they treat each species separately, include little, if any, spatial structure, and may not adequately quantify uncertainty. These assumptions can introduce bias and can lead to incorrect inferences. This thesis is about more realistic models and their inference. This realism may be incorporated by explicitly modelling complex processes, or by admitting our uncertainty and modelling it correctly.  We develop an agent-based model that can describe fish populations as a collection of individuals which differ in their growth, maturation, migration, and mortality. The aim of this model is to better capture the richness in natural processes that determine fish abundance and subsequent population response to anthropogenic removals. However, this detail comes at considerable computational cost. A single model run can take many hours, making inference using standard methods impractical. We apply this model to New Zealand snapper (Pagurus auratus) in northern New Zealand.  Next, we developed an age-structured state-space model. We suggest that this sophisticated model has the potential to better represent uncertainty in stock assessment. However, it pushes the boundaries of the current practical limits of computing and we admit that its practical application remains limited until the MCMC mixing issues that we encountered can be resolved.   The processes that underpin agent-based models are complex and we may need to seek new sources of data to inform these types of models. To make a start here we derive a state-space model to estimate the path taken by individual fish from the day they are tagged to the day of their recapture. The model uses environmental information collected using pop-up satellite archival tags. We use tag recorded depth and oceanographic temperature to estimate the location at any given time. We apply this model to Antarctic toothfish (Dissostichus mawsoni) in the Ross Sea.  Finally, to reduce the computational burden of agent-based models we use Bayesian emulation. This approach replaces the simulation model with an approximating algorithm called an emulator. The emulator is calibrated using relatively few runs of the original model. A good emulator provides a close approximation to the original model and has significant speed gains. Thus, inferences become tractable.  We have made the first steps towards developing a tractable approach to fisheries modelling in complex settings through the creation of realistic models, and their emulation. With further development, Bayesian emulation could result in the increased ability to consider and evaluate innovative methods in fisheries modelling. Future avenues for application and exploration range from spatial and multi species models, to ecosystem-based models and beyond.</p>

scholarly journals Particle Filtering: A Priori Estimation of Observational Errors of a State-Space Model with Linear Observation Equation

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1445
Author(s):  
Rodi Lykou ◽  
George Tsaklidis
Keyword(s):  
State Space ◽  
Particle Filtering ◽  
A Priori ◽  
State Space Model ◽  
Computational Cost ◽  
The State ◽  
Observation Equation ◽  
Basic Algorithm ◽  
Space Model ◽  
Observational Errors

Observational errors of Particle Filtering are studied over the case of a state-space model with a linear observation equation. In this study, the observational errors are estimated prior to the upcoming observations. This action is added to the basic algorithm of the filter as a new step for the acquisition of the state estimations. This intervention is useful in the presence of missing data problems mainly, as well as sample tracking for impoverishment issues. It applies theory of Homogeneous and Non-Homogeneous closed Markov Systems to the study of particle distribution over the state domain and, thus, lays the foundations for the employment of stochastic control against impoverishment. A simulating example is quoted to demonstrate the effectiveness of the proposed method in comparison with existing ones, showing that the proposed method is able to combine satisfactory precision of results with a low computational cost and provide an example to achieve impoverishment prediction and tracking.

scholarly journals A structural model with interventions for new Zealand sawn timber production

2006 ◽  
Vol 2006 ◽  
pp. 1-12
Author(s):  
Dongwen Luo ◽  
Geoffrey Jones ◽  
Judith Dennis
Keyword(s):  
New Zealand ◽  
State Space ◽  
Structural Changes ◽  
Structural Model ◽  
Seasonal Pattern ◽  
State Space Model ◽  
Timber Production ◽  
Space Model ◽  
Future Production ◽  
Sawn Timber

Timber production in New Zealand was privatized in 1987. We examine the effects of this change on the level of New Zealand sawn timber production, and changes in the seasonal pattern, using a state-space model with intervention variables. We describe the formulation and estimation of the state-space model, and show how it can be used to examine both the structural changes around the time of privatization and the gradually evolving seasonal pattern in production. We also show how the model can be used to forecast future production.

Stock assessment and management of blackthroat seaperch Doederleinia seaperch using Bayesian state-space model

2019 ◽  
Vol 55 (2) ◽  
pp. 95-104
Author(s):  
Ji Hoon CHOI ◽  
Do Hoon KIM ◽  
Min-Je CHOI ◽  
Hee Joong KANG ◽  
Young Il SEO ◽  
...  
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
State Space Model ◽  
Space Model

Development of L1-norm sliding mode observer for sensor fault diagnosis of an industrial gas turbine

2021 ◽  
pp. 095965182199617
Author(s):  
Mahyar Akbari ◽  
Abdol Majid Khoshnood ◽  
Saied Irani
Keyword(s):  
Fault Detection ◽  
State Space ◽  
Gas Turbine ◽  
Sliding Mode ◽  
State Space Model ◽  
Sensor Fault ◽  
Space Model ◽  
Decision Logic ◽  
Sensor Fault Detection ◽  
Industrial Gas Turbine

In this article, a novel approach for model-based sensor fault detection and estimation of gas turbine is presented. The proposed method includes driving a state-space model of gas turbine, designing a novel L1-norm Lyapunov-based observer, and a decision logic which is based on bank of observers. The novel observer is designed using multiple Lyapunov functions based on L1-norm, reducing the estimation noise while increasing the accuracy. The L1-norm observer is similar to sliding mode observer in switching time. The proposed observer also acts as a low-pass filter, subsequently reducing estimation chattering. Since a bank of observers is required in model-based sensor fault detection, a bank of L1-norm observers is designed in this article. Corresponding to the use of the bank of observers, a two-step fault detection decision logic is developed. Furthermore, the proposed state-space model is a hybrid data-driven model which is divided into two models for steady-state and transient conditions, according to the nature of the gas turbine. The model is developed by applying a subspace algorithm to the real field data of SGT-600 (an industrial gas turbine). The proposed model was validated by applying to two other similar gas turbines with different ambient and operational conditions. The results of the proposed approach implementation demonstrate precise gas turbine sensor fault detection and estimation.

Modeling of CCLP in koryo extract production

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ji Chol ◽  
Ri Jun Il
Keyword(s):  
Process Control ◽  
Medical Care ◽  
State Space ◽  
State Space Model ◽  
The State ◽  
Space Model ◽  
Effective Components ◽  
Counter Current

Abstract The modeling of counter-current leaching plant (CCLP) in Koryo Extract Production is presented in this paper. Koryo medicine is a natural physic to be used for a diet and the medical care. The counter-current leaching method is mainly used for producing Koryo medicine. The purpose of the modeling in the previous works is to indicate the concentration distributions, and not to describe the model for the process control. In literature, there are no nearly the papers for modeling CCLP and especially not the presence of papers that have described the issue for extracting the effective components from the Koryo medicinal materials. First, this paper presents that CCLP can be shown like the equivalent process consisting of two tanks, where there is a shaking apparatus, respectively. It allows leachate to flow between two tanks. Then, this paper presents the principle model for CCLP and the state space model on based it. The accuracy of the model has been verified from experiments made at CCLP in the Koryo Extract Production at the Gang Gyi Koryo Manufacture Factory.

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