Modeling inflow rates for the water exchange management in semi-intensive aquaculture ponds (original) (raw)

Fuzzy logic based control system for fresh water aquaculture: A MATLAB based simulation approach

Serbian Journal of Electrical Engineering, 2015

Fuzzy control is regarded as the most widely used application of fuzzy logic. Fuzzy logic is an innovative technology to design solutions for multiparameter and non-linear control problems. One of the greatest advantages of fuzzy control is that it uses human experience and process information obtained from operator rather than a mathematical model for the definition of a control strategy. As a result, it often delivers solutions faster than conventional control design techniques. The proposed system is an attempt to apply fuzzy logic techniques to predict the stress factor on the fish, based on line data and rule base generated using domain expert. The proposed work includes a use of Data acquisition system, an interfacing device for on line parameter acquisition and analysis, fuzzy logic controller (FLC) for inferring the stress factor. The system takes stress parameters on the fish as inputs, fuzzified by using FLC with knowledge base rules and finally provides single output. All...

Assisted management of water exchange in traditional semi-intensive aquaculture ponds

Computers and Electronics in Agriculture, 2014

Grid gates with multiple sharp-crested rectangular orifices are used to control manually water discharge from branch channels to semi-intensive aquaculture ponds. Experimental and analytical analysis related to the discharge characteristics of these grid gates under submerged flow conditions have been presented in this paper with the objective to integrate the results in an support system to control the water exchange management. Experimental analysis was carried out in the laboratory using a scaled model. Steady-state hydraulic data were measured and collected for each tested grid gate considering different orifices number and flow rates. Multiple linear regression (MLR), factorial regression (FR), polynomial regression (PR), hybrid model (PR + FR) and generalized linear model (GLM) were evaluated to determine the relationship between the coefficient of discharge C d and the non-dimensional parameters x=h 2 1 , b/h 1 and h 3 /h 1 (x is the total cross section of discharge; h 1 is the upstream water level of the grid gate; h 3 is the downstream water level of the grid gate; and b is the width of the channel) which were obtained by the analysis dimensional. Of all these approaches, the best fits were obtained using a FR + PR hybrid model and a GLM model with only two non-dimensional parameters x=h 2 1 and h 3 /h 1 as independent variables. These models produced errors not higher than ±3%. The best GLM model and the aquaculturist knowledge in relation to the management of water exchange were integrated in a computer program namely 'Gate management' which was implemented in the ACUIGES system.

Introduction to computer modeling of aquaculture pond ecosystems

Aquaculture Research, 1988

The application of computer modelling to the study of aquaculture ponds is reviewed. Two basic types of models are identified: empirical and mechanistic. In empirical modeis, the pond system is treated as a 'black box', and the relationship between inputs and outputs is determined by statistical analysis of data. In mechanistic models ('internally descriptive'), processes taking place within the pond are identified and described mathematically. A framework for the development of a mechanistic model of an aquaculture pond is presented. Sample formulations for some critical variables are discussed.

Development of farm pond operational modeling using Neuro-Fuzzy technique

Journal of Applied and Natural Science

Study was conducted to derive operational model for a farm pond of 3000 cubic meter capacity at Center for protected cultivation technology (CPCT), Indian Agricultural Research Institute, New Delhi, India which was the important source of irrigation water of the farm of the area 10 ha. The Neuro-Fuzzy approach was used to develop the operational model and to derive operational rules for proper irrigation scheduling of the horticultural crops grown at CPCT. Based upon the inputs like crop water requirement, evaporation losses and farm pond inflow the model predicting outflow of the reservoir was developed. The developed model was having high accuracy and predictability when tested statistically. The coefficient of determination (R2) was found to be 0.96, whereas the model efficiency (E) was 0.97 which shows the high reliability of the model. The operating rules which were of ‘If-Then’ form were also developed which would lead to better management of the farm pond system and would...

Water level control of small-scale recirculating aquaculture system with protein skimmer using fuzzy logic controller

IAES International Journal of Robotics and Automation (IJRA), 2023

The recirculating aquaculture system (RAS) is a land-based aquaculture facility, either open-air or indoors, that minimizes water consumption by filtering, adapting, and reusing water. Solid organic matter from fish waste and food waste directly becomes waste that needs to be eliminated because it is a source of increasing total ammonia nitrogen (TAN), total suspended solids (TSS), total dissolved solids (TDS), and also has an impact on reducing dissolved oxygen (DO). RAS requires a water level control system so the fish tank does not experience water shortages or floods, disrupting the aquatic aquaculture ecosystem. In this study, small-scale RAS is modeled using a 3-coupled tanks system approach with a tank configuration that follows the most straightforward RAS water recirculation process (fish tank, mechanic filter, biofilter). Clean water from the reservoir flows into the fish tank through a protein skimmer. This study applies the fuzzy logic controller (FLC) to control the water level in the protein skimmer and biofilter tanks by controlling the position of several valves where the placement positions of the valves have been determined according to system requirements. The study results show that the tuned single-input FLC has the best average output response characteristics with 𝑡𝑠=50, ℎ1𝑠𝑠=49.98, 𝑒𝑠𝑠=0.02 in protein skimmer and 𝑡𝑠=4700, ℎ1𝑠𝑠=39.75, 𝑒𝑠𝑠=0.25 in the tank system.

A Hybrid Neural Network and Genetic Algorithm Model for Predicting Dissolved Oxygen in an Aquaculture Pond

The prediction for dissolved oxygen (DO) in aquaculture ponds is a problem of multi-variables, nonlinearity and long-time lag. Neural networks (NNs) have become one of ideal tools in modeling nonlinear relationship between inputs and outputs. In this work, GA-LM, a neural network model combining Levenberg-Marquardt(LM) algorithm and Genetic Algorithm (GA) was developed for predicting DO in an aquaculture pond at Dalian, China. LM was used to train NNs, showing faster convergence rate. The network architecture was optimized by GA. The performance of GA-LM has been compared with that of conventional Back-Propagation (BP) algorithm and Levenberg-Marquardt(LM) algorithm. The comparison indicates that the predicted DO values using GA-LM model are in good agreement with the measured data. It is demonstrated here that the model is capable of predicting DO accurately, and can offer stronger and better performance than conventional neural networks when used as a quick interpolation and extrapolation tool.

Design of a Fuzzy Logic Controller for Optimal African Catfish Water Production

MEKATRONIKA

Fish, unlike other animals, feed and defecate inside the same water where they live. When water quality depreciates, consumed feed is not properly converted into body flesh, poor growth is recorded, fish survival is affected and ultimately massive fish deaths may occur. In fish production, key water quality parameters which need to be continually monitored and controlled are temperature, dissolved oxygen (DO), pH, and ammonia. These parameters are highly non-linear, and thus difficult and expensive to use conventional controllers. Fuzzy logic controllers can suitably adapt to non-linearity because it uses sentences for control actions rather than equations. FisPro (Fuzzy Inference System Professional) is used to create fuzzy inference system (FIS)/ fuzzy logic controller (FLC) for simulating physical or biological systems. The selected water quality parameter are temperature, 14 to 45oC, potency of hydrogen (pH), 0 to 14, and turbidity, 1 to 5. At a pH of 3.5 and 39oC, the aerator s...

NEURAL NETWORK AND ITS APPLICATION IN AQUACULTURE

Introduction: In the-past decades the researchers and managers have used empirical , statistical models or complicated mathematical models predict the consequences of management regimes or actions, and to assist in decision~making. These models are K· exPJ·es~sed as mathematical equations. Howeller, some decision-ma~ing processes contain litative components that do not lend themselves to being integrated into mathematical equations. As [1] point out, decision making in natural resources often leads to complexities ~"bElVOlld the reach of empirical statistical techniques, and requires approaches that are l"~rlm<"rlTlp~ more heuristic than algorithmic. In many cases, statistical models cannot give results and to solve the more complex problems in fish yield prediction.