scholarly journals Gaussian Distribution Model for Detecting Dangerous Operating Conditions in Industrial Fish Farming

2021 ◽  
Vol 11 (13) ◽  
pp. 5875
Author(s):  
Luís Cicero Bezerra da Silva ◽  
Bruna Daniela Mendes Lopes ◽  
Isidro Manuel Blanquet ◽  
Carlos Alberto Ferreira Marques
Keyword(s):  
Gaussian Distribution ◽  
Fish Farming ◽  
Operating Conditions ◽  
Distribution Model ◽  
Aquaculture Industry ◽  
Promising Solution ◽  
Monitoring Technologies ◽  
Chemical And Biological Systems ◽  
Probabilistic Nature ◽  
Gaussian Distribution Model

The development of better monitoring technologies, the early combat of outbreaks, massive mortality, and promoting sustainability are challenges that the aquaculture industry still faces, and the development of solutions for this is an open problem. In this paper, focusing our attention on monitoring technologies as a promising solution to these issues, we report a Gaussian distribution model for detecting dangerous operating conditions in industrial fish farming. This approach allows us to indicate through a 2D image visualization when fish production is under normal, warning, or dangerous operating conditions. Furthermore, our proposed method has promising possibilities for application in the most varied fields of science, given that the mathematical procedure described allows us to discover the fundamental statistical structure of physical, chemical, and biological systems governed by laws of a probabilistic nature.

Evaluation of the Hourly Global Solar Radiation on a Horizontal Plane for Two Sites in Algeria

2014 ◽  
Vol 925 ◽  
pp. 641-645 ◽  
Author(s):  
Mohamed Salmi ◽  
Hassen Bouzgou ◽  
Yarub Al-Douri ◽  
Abdelhakim Boursas
Keyword(s):  
Solar Radiation ◽  
Gaussian Distribution ◽  
Horizontal Plane ◽  
Experimental Validation ◽  
Global Solar Radiation ◽  
Distribution Model ◽  
Experimental Assessment ◽  
Precise Prediction ◽  
Gaussian Distribution Model ◽  
Modelling Approach

We present three models for the estimation of hourly global solar radiation for two sites in Algeria, namely: Djelfa (Latitude 34.68°N, Longitude 3.25°E, Altitude 1126 (m)) and Ain Bessem (Latitude 36.31°N, Longitude 3.67°E, Altitude 629 (m)). The models are: the Gaussian distribution model, the model by Collares-Pereira-RabI and the H.A. model (Hourly absolute modelling approach). The experimental assessment was done using recorded values of the hourly global solar radiation on a horizontal plane during the period 2000-2004. The obtained results show a close similarity between the solar radiation values calculated by the three models and the measured values, especially for the first model. The experimental validation shows promising results for the estimation and precise prediction of the hourly global solar radiation.

Numerical Simulation and Experimental Research on MAG Surfacing Deposited with Electro-Magnetic Stirring Controlling

2010 ◽  
Vol 102-104 ◽  
pp. 407-411 ◽  
Author(s):  
Guo Ji Zhao ◽  
Qian Luo ◽  
Xiang Jie Wang ◽  
Jian Luo
Keyword(s):  
Magnetic Field ◽  
Numerical Simulation ◽  
Gaussian Distribution ◽  
Mag Welding ◽  
Distribution Model ◽  
Welding Arc ◽  
Magnetic Stirring ◽  
Electro Magnetic ◽  
Gaussian Distribution Model ◽  
Additional Magnetic Field

Numerical simulation and deposited experiment of MAG welding are carried out on the conditions of Electro-Magnetic Stirring (EMS) in this paper. Based on the research of EMS welding arc action, a simple EMS-MAG welding Gaussian distribution model using whole heat flux density is established, which MAG welding arc and droplet transfer are regarded as one integrated system. The important additional magnetic field parameter in EMS-MAG surfacing deposited welding is considered in this model. The computer-aided arc measurement system is used to analyze the effects of additional magnetic field in MAG welding. Effects of excitation current on welding penetration and width are analyzed by deposited experiments. Many deposited experiments are used to adjust model parameters and verify the simulation results. By defining key parameter and optimizing the model on the basis of experimental data, it can improve the simulation accuracy effectively. The results show that the established Gaussian distribution model can be used to simulate EMS-MAG welding process.

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