scholarly journals Substituting model-based indicators in Harvest Control Rules by observations using fuzzy logic methodology

2017 ◽  
Vol 75 (3) ◽  
pp. 977-987
Author(s):  
Arne Eide
Keyword(s):  
Fuzzy Logic ◽  
Mathematical Models ◽  
Stock Assessment ◽  
Decision Rules ◽  
Initial Information ◽  
Stock Size ◽  
Control Rules ◽  
Stock Biomass ◽  
Size Evaluation ◽  
Harvest Control Rules

Abstract Harvest Control Rules are predefined heuristic decision rules to provide quota advices for managed fisheries. Frequently statistical methods and biological assumptions expressed in mathematical models, are used to provide the Harvest Control Rules with initial information (indicators values). The aim of this article is to investigate a possible way forward of replacing these inputs by quantities of measurable observations, e.g. catch-at-age statistics. The article presents a method by which recruitment indexes and stock biomass indicators are obtained by non-parametric use of annual catch-at-age records, without filtering the raw data (observations) through mathematical models. Two related methods, applied on three empirical cases, are provided: First, showing that recruitment strengths of the Northeast Arctic cod, haddock, and saithe stocks, obtained by fuzzy logic methodology, are satisfactory captures by the use of catch-at-age data. Second, stock size indicators are estimated for the three species by the same catch-at-age data. The second task turns out to be more challenging than the first, but also in the case of stock size evaluation, the suggested procedure provides reasonable results when compared to standard stock assessment methods.

Assessing the sensitivity of data-limited methods (DLMs) to the estimation of life-history parameters from length–frequency data

2018 ◽  
Vol 75 (10) ◽  
pp. 1563-1572 ◽  
Author(s):  
Ming Sun ◽  
Chongliang Zhang ◽  
Yong Chen ◽  
Binduo Xu ◽  
Ying Xue ◽  
...  
Keyword(s):  
Life History ◽  
Stock Assessment ◽  
Stock Management ◽  
Larimichthys Polyactis ◽  
Life History Parameters ◽  
Control Rules ◽  
Strategy Evaluation ◽  
Management Procedures ◽  
Spawning Potential Ratio ◽  
Harvest Control Rules

Data-limited methods (DLMs) in stock assessment may provide potential critical information for data-limited stock management. However, the sensitivity of those methods to life-history parameters is largely unknown, resulting in extra uncertainty and consequent risks. In the present study, we designed six parallel workflows (WFs) to incorporate classic and state-of-the-art methods of estimating life-history parameters and examined their influences on the assessment of small yellow croaker (Larimichthys polyactis) in Haizhou Bay, China. The sensitivity was evaluated with three objectives: (i) the evaluation of stock status with the spawning potential ratio following different assumptions; (ii) the length-based harvest control rules derived from three management procedures; and (iii) the management performance of these harvest control rules with simulation of management strategy evaluation. The results showed considerable sensitivity regarding the three objectives to the estimations with different WFs, indicating the previous practice of credulously accepting empirical values and indiscriminately selecting references are inadvisable. We also identified the most appropriate WFs used for different purposes with limited data, aiming to provide more reliable inputs for effective fisheries management.

scholarly journals Objectives and harvest control rules in the management of the fishery of Norwegian spring-spawning herring

2009 ◽  
Vol 66 (8) ◽  
pp. 1793-1799 ◽  
Author(s):  
Sigurd Tjelmeland ◽  
Ingolf Røttingen
Keyword(s):  
Stock Assessment ◽  
Maximum Sustainable Yield ◽  
Assessment Model ◽  
Main Element ◽  
Management Objectives ◽  
Control Rules ◽  
Harvest Control Rule ◽  
Stock Recruitment ◽  
Harvest Control Rules

Abstract Tjelmeland, S., and Røttingen, I. 2009. Objectives and harvest control rules in the management of the fishery of Norwegian spring-spawning herring. – ICES Journal of Marine Science, 66: 1793–1799. The main element in the management of the Norwegian spring-spawning herring, as implemented by the coastal states, is to conduct the fishery based on a maximum fishing mortality (F) of 0.125. As the appropriateness of this rule (given the stated objectives) has not yet been tested thoroughly, we set out to do this by long-term simulations, in which we applied a range of alternative stock–recruitment relationships. These different relationships are estimated from historical replicates of the stock, as calculated by the herring-stock assessment model SeaStar. During prognostic simulations, a recruitment model is selected probabilistically for each historical replicate based on Akaike weights. We evaluate whether the management objectives are met by applying the present harvest control rule. Results are given for the current assessment option of natural mortality (M = 0.5) in the oldest aggregated age group and for the assessment option used in 2005 and earlier (M = 0.15). These show that perceptions of the long-term yield differ considerably and that the current management is somewhat on the conservative side from the perspective of maximum sustainable yield.

scholarly journals Performance of harvest control rules in a variable environment

2010 ◽  
Vol 67 (5) ◽  
pp. 1051-1062 ◽  
Author(s):  
Thomas Brunel ◽  
Gerjan J. Piet ◽  
Ralf van Hal ◽  
Christine Röckmann
Keyword(s):  
Dynamic Models ◽  
Generalized Additive Models ◽  
Maximum Sustainable Yield ◽  
Additive Models ◽  
Precautionary Approach ◽  
Variable Environment ◽  
Control Rules ◽  
Stock Biomass ◽  
Stock Recruitment ◽  
Harvest Control Rules

AbstractBrunel, T., Piet, G. J., van Hal, R., and Röckmann, C. 2010. Performance of harvest control rules in a variable environment. – ICES Journal of Marine Science, 67: 1051–1062. Population dynamic models used for fisheries management assume that stocks are isolated entities, ignoring the influence of environmental factors on stock productivity. An operating model parameterized for North Sea cod, plaice, and herring is developed, in which the link between recruitment and environment is assumed to be known and described by generalized additive models. This tool is used to compare the performance of harvest control rules (HCRs) when recruitment is independent of the environment or when recruitment is affected by an environment varying according to different scenarios. The first HCR exploited the stock with a fixed fishing mortality (F) corresponding to maximum sustainable yield, and in the second HCR, F was set equal to the precautionary approach F (i.e. Fpa), but reduced from Fpa when stock biomass fell below Bpa. The performance of the HCRs altered only slightly in a randomly varying environment compared with a constant one. For a detrimental change in the environment, however, no HCR could prevent a massive decrease in stock size. The performance of the HCRs was also influenced by the stock characteristics, such as recruitment variability or the shape of the stock–recruitment relationship. The performance of “environmental” HCRs (eHCRs), in which F varies depending on environmental conditions, was compared with that of conventional HCRs. The gain in using the eHCR was small, except for a detrimental change in the environment, where the eHCR performed markedly better than a conventional HCR. The benefits of using the eHCR were the greatest for the stock with the strongest environment–recruitment relationship.

The roles of biological reference points and operational control points in management procedures for the sablefish (Anoplopoma fimbria) fishery in British Columbia, Canada

2013 ◽  
Vol 40 (4) ◽  
pp. 318-328 ◽  
Author(s):  
SEAN P. COX ◽  
ALLEN R. KRONLUND ◽  
ASHLEEN J. BENSON
Keyword(s):  
British Columbia ◽  
Stock Assessment ◽  
Reference Points ◽  
Control Points ◽  
Operational Control ◽  
Short Term ◽  
Anoplopoma Fimbria ◽  
Control Rules ◽  
Management Procedures ◽  
Harvest Control Rules

SUMMARYBiological reference points (BRPs) in fisheries policy are typically sensitive to stock assessment model assumptions, thus increasing uncertainty in harvest decision-making and potentially blocking adoption of precautionary harvest policies. A collaborative management strategy evaluation approach and closed-loop simulation modelling was used to evaluate expected fishery economic and conservation performance of the sablefish (Anoplopoma fimbria) fishery in British Columbia (Canada), in the presence of uncertainty about BRPs. Comparison of models derived using two precautionary harvest control rules, which each complied with biological conservation objectives and short-term economic objectives given by industry, suggested that both rules were likely to avert biomass decline below limit BRPs, even when stock biomass and production were persistently overestimated by stock assessment models. The slightly less conservative, industry-preferred harvest control rule also avoided short-term economic losses of c. CAN$ 2.7–10 million annually, or 10–50% of current landed value. Distinguishing between the role of BRPs in setting fishery conservation objectives and operational control points that define harvest control rules improved the flexibility of the sablefish management system, and has led to adoption of precautionary management procedures.

scholarly journals Implementing the precautionary approach into fisheries management: Making the case for probability-based harvest control rules

2020 ◽  
Author(s):  
Tobias K. Mildenberger ◽  
Casper W. Berg ◽  
Alexandros Kokkalis ◽  
Adrian R. Hordyk ◽  
Chantel Wetzel ◽  
...  
Keyword(s):  
Fisheries Management ◽  
Management Strategies ◽  
Reference Points ◽  
Production Model ◽  
Scientific Uncertainty ◽  
Precautionary Approach ◽  
Control Rules ◽  
Stock Biomass ◽  
Harvest Control Rules

AbstractThe precautionary approach to fisheries management advocates for risk-averse management strategies that include biological reference points as well as decision rules and account for scientific uncertainty. In this regard, two approaches have been recommended: (i) harvest control rules (HCRs) with threshold reference points to safeguard against low stock biomass, and (ii) the P* method, a ‘probability-based HCR’ that reduces the catch limit as a function of scientific uncertainty (i.e. process, model, and observation uncertainty). This study compares the effectiveness of these precautionary approaches in recovering over-exploited fish stocks with various life-history traits and under a wide range of levels of scientific uncertainty. We use management strategy evaluation based on a stochastic, age-based operating model with quarterly time steps and a stochastic surplus production model. The results show that the most effective HCR includes both a biomass threshold as well as the P* method, and leads to high and stable long-term yield with a decreased risk of low stock biomass. For highly dynamics stocks, management strategies that aim for higher biomass targets than the traditionally used BMSY result in higher long-term yield. This study makes the case for probability-based HCRs by demonstrating their benefit over deterministic HCRs and provides a list of recommendations regarding their definition and implementation.

scholarly journals ANALISIS RULE INFERENSI FUZZY MAMDANI DALAM MENENTUKAN IPK AKHIR

2017 ◽  
Vol 1 (1) ◽  
pp. 22
Author(s):  
Khairul Saleh
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Mathematical Models ◽  
Dynamic Systems ◽  
Fuzzy Systems ◽  
Chaotic Dynamics ◽  
Complex Dynamic ◽  
Grade Point ◽  
Complex Dynamic Systems ◽  
Decision Making System

Abstract - In the world of education to achieve the level of success, of course, they have a benchmark for the success of students, one of them is the Grade Point Average (GPA). The purpose of this study is to determine the final GPA so that later it can be used as a reference to predict the success rate of students. The issue of decision-making systems using Fuzzy systems is very suitable for definite reasoning or estimation, especially for systems with strict mathematical models that are difficult to get a definite decision. Fuzzy logic can be used to describe a system of chaotic dynamics, and fuzzy logic can be useful for complex dynamic systems where solutions to common mathematical models cannot work well. The Mamdani method computes efficiently and works well with optimization and adaptive techniques, which makes it very good in control problems, especially for dynamic non-linear systems. Keywords - Cumulative Achievement Index (GPA), fuzzy system, decision making system, mamdani information

scholarly journals Clinical Outcome Prediction in Aneurysmal Subarachnoid Hemorrhage Using Bayesian Neural Networks with Fuzzy Logic Inferences

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Benjamin W. Y. Lo ◽  
R. Loch Macdonald ◽  
Andrew Baker ◽  
Mitchell A. H. Levine
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Subarachnoid Hemorrhage ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Hidden Variables ◽  
Decision Rules ◽  
Bayesian Neural Networks ◽  
Prognostic System ◽  
History Of ◽  
Prediction Approach

Objective. The novel clinical prediction approach of Bayesian neural networks with fuzzy logic inferences is created and applied to derive prognostic decision rules in cerebral aneurysmal subarachnoid hemorrhage (aSAH).Methods. The approach of Bayesian neural networks with fuzzy logic inferences was applied to data from five trials of Tirilazad for aneurysmal subarachnoid hemorrhage (3551 patients).Results. Bayesian meta-analyses of observational studies on aSAH prognostic factors gave generalizable posterior distributions of population mean log odd ratios (ORs). Similar trends were noted in Bayesian and linear regression ORs. Significant outcome predictors include normal motor response, cerebral infarction, history of myocardial infarction, cerebral edema, history of diabetes mellitus, fever on day 8, prior subarachnoid hemorrhage, admission angiographic vasospasm, neurological grade, intraventricular hemorrhage, ruptured aneurysm size, history of hypertension, vasospasm day, age and mean arterial pressure. Heteroscedasticity was present in the nontransformed dataset. Artificial neural networks found nonlinear relationships with 11 hidden variables in 1 layer, using the multilayer perceptron model. Fuzzy logic decision rules (centroid defuzzification technique) denoted cut-off points for poor prognosis at greater than 2.5 clusters.Discussion. This aSAH prognostic system makes use of existing knowledge, recognizes unknown areas, incorporates one's clinical reasoning, and compensates for uncertainty in prognostication.

Nonstationarity of Production Relationships in Exploited Populations

1987 ◽  
Vol 44 (S2) ◽  
pp. s156-s165 ◽  
Author(s):  
Carl J. Walters
Keyword(s):  
Environmental Changes ◽  
Historical Data ◽  
Stock Assessment ◽  
Policy Implications ◽  
Data Sets ◽  
Stock Structure ◽  
Stock Size ◽  
Rate Processes ◽  
And Shifts ◽  
Time Invariant

Stock assessment usually proceeds from the assumption that there are time-invariant relationships between stock size and rate processes such as recruitment, although such relationships are difficult to discern due to noise caused by factors other than stock size. There are good biological reasons not to trust this assumption in exploited populations, where persistent environmental changes and shifts in stock structure may cause various parameters to change. Graphical and statistical procedures can be used to detect this nonstationarity in historical data sets for which stock size has varied so as to repeatedly sample a range of sizes. The policy implications of nonstationarity depend on whether the changes are clearly observable as deviations from known, Song-term baseline responses. If the changes are observable, it is usually best to pretend that the current deviation will persist unless strong constraints on policy change make it necessary to plan for changes that may occur far into the future. If the changes are not observable (the usual case), then it is necessary to make a difficult policy choice between passively waiting for informative stock responses versus actively experimenting with harvest rates so as to quickly get information about responses over a range of stock sizes.

Methodology of Developing Mathematical Models with Fuzzy Logic Elements for Quality Indices Control

2013 ◽  
Vol 436 ◽  
pp. 374-381 ◽  
Author(s):  
Alexey Korchunov ◽  
Mikhail Chukin ◽  
Aleksandr Lysenin
Keyword(s):  
Fuzzy Logic ◽  
Mathematical Models ◽  
Preference Relation ◽  
Fuzzy Relation ◽  
Quality Indices ◽  
New Models ◽  
Acting Process ◽  
Metal Products ◽  
Process Operations ◽  
Fuzzy Logic Theory

Advantages of applying fuzzy logic theory to metal products quality indices control in development of new models and in improvement of acting process operations are shown. It is proved that it is appropriate to determine fuzzy relation as preference relation in process of handling products quality indices in process operations. Elaboration of algorithm of handling mathematical models with fuzzy logic elements to control quality indices is undertaken. Methodology of mathematical models development with fuzzy logic elements for metal products quality indices control is created. Process of metal products quality indices control on the basis of models with fuzzy logic elements is illustrated.

scholarly journals Assessing global marine fishery status with a revised dynamic catch-based method and stock-assessment reference points

2012 ◽  
Vol 69 (8) ◽  
pp. 1491-1500 ◽  
Author(s):  
Sean C. Anderson ◽  
Trevor A. Branch ◽  
Daniel Ricard ◽  
Heike K. Lotze
Keyword(s):  
Stock Assessment ◽  
Original Method ◽  
Reference Points ◽  
Marine Science ◽  
Marine Fishery ◽  
Stock Biomass ◽  
Exploitation Rate ◽  
Realistic Assessment ◽  
Fishery Status

Abstract Anderson, S. C., Branch, T. A., Ricard, D., and Lotze, H. K. 2012. Assessing global marine fishery status with a revised dynamic catch-based method and stock-assessment reference points. – ICES Journal of Marine Science, 69: . The assessment of fishery status is essential for management, yet fishery-independent estimates of abundance are lacking for most fisheries. Methods exist to infer fishery status from catches, but the most commonly used method is biased towards classifying fisheries as overexploited or collapsed through time and does not account for still-developing fisheries. We introduce a revised method that overcomes these deficiencies by smoothing catch series iteratively, declaring fisheries developing within three years of peak catch, and calibrating thresholds to biological reference points. Compared with status obtained from stock-assessment reference points for 210 stocks, our approach provides a more realistic assessment than the original method, but cannot be perfect because catches are influenced by factors other than biomass. Applied to FAO catches, our method suggests in 2006 32% of global fisheries were developing, 27% fully exploited, 25% overexploited, and 16% collapsed or closed. Although less dire than previous assessments, this still indicates substantial numbers of overexploited stocks. Probably because median exploitation rate decreased since 1992, our catch-based results do not reflect recent stabilization of assessed-stock biomass. Whether this outlook also applies to unassessed stocks can only be revealed with increased or more representative collection of biomass- and exploitation-rate trends.

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