scholarly journals Fuzzy system to evaluate performance and the physiological responses of piglets raised in the farrowing house with different solar heating systems

2019 ◽  
Vol 72 (1) ◽  
pp. 8729-8742
Author(s):  
Flavio Alves Damasceno ◽  
Carlos Eduardo Alves Oliveira ◽  
Jairo Alexander Osório Saraz ◽  
Lucas Hernrique Pedrozo Abreu ◽  
Patricia Ferreira Ponciano Ferraz
Keyword(s):  
Fuzzy System ◽  
Thermal Environment ◽  
Physiological Responses ◽  
Fuzzy Model ◽  
Solar Heating ◽  
Productive Performance ◽  
Validation Data ◽  
Heating Systems ◽  
Heating Efficiency ◽  
Solar Heater

The present work aims to develop a mathematical model, based on fuzzy set theory, for predicting performance and the physiological responses of piglets raised in the farrowing house with different solar heating systems. To do this, a solar heater prototype was constructed using alternative materials and the heating efficiency was compared with a commercial solar heater system. In order to thermally evaluate the heaters, temperature sensors were installed in the inlet and outlet pipes of each floor and thermal reservoir. The fuzzy system was developed and the variables dry air bulb temperature (Tbs) and relative humidity (RH) of the air were defined as inputs. Based on the input variables, the fuzzy system predicts the productive performance (weight gain - WG) and physiological responses (respiratory rate - RR, rectal temperature –RT, and skin temperature - ST) of piglets raised in an environment with solar heating. Based on the results, the fuzzy model was adequate for predicting the physiological responses and productive performance of piglets, presenting low standard deviation and high correlation with the validation data. This model can be used to assist producers in decision making, especially regarding maintaining animal welfare while the thermal environment changes.

scholarly journals Prediction of free-stall occupancy rate in dairycattle barns through fuzzy sets

2013 ◽  
Vol 33 (6) ◽  
pp. 1079-1089 ◽  
Author(s):  
Alessandro T. Campos ◽  
Jaqueline de O. Castro ◽  
Leonardo Schiassi ◽  
Tadayuki Yanagi Junior ◽  
Maria de Fátima Á. Pires ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Fuzzy System ◽  
Fuzzy Model ◽  
Simulated Data ◽  
Occupancy Rate ◽  
Validation Data ◽  
Average Percentage ◽  
Planning And Design ◽  
Input Variables ◽  
Globe Temperature

The goal of this study was to develop a fuzzy model to predict the occupancy rate of free-stalls facilities of dairy cattle, aiding to optimize the design of projects. The following input variables were defined for the development of the fuzzy system: dry bulb temperature (Tdb, °C), wet bulb temperature (Twb, °C) and black globe temperature (Tbg, °C). Based on the input variables, the fuzzy system predicts the occupancy rate (OR, %) of dairy cattle in free-stall barns. For the model validation, data collecting were conducted on the facilities of the Intensive System of Milk Production (SIPL), in the Dairy Cattle National Research Center (CNPGL) of Embrapa. The OR values, estimated by the fuzzy system, presented values of average standard deviation of 3.93%, indicating low rate of errors in the simulation. Simulated and measured results were statistically equal (P>0.05, t Test). After validating the proposed model, the average percentage of correct answers for the simulated data was 89.7%. Therefore, the fuzzy system developed for the occupancy rate prediction of free-stalls facilities for dairy cattle allowed a realistic prediction of stalls occupancy rate, allowing the planning and design of free-stall barns.

scholarly journals Use of alternative tiles in the free-range broilers rearing: thermal environment, productive performance and physiological responses

2021 ◽  
Vol 9 (1) ◽  
pp. 1-13
Author(s):  
Mônica Patrícia Maciel ◽  
Cinara da Cunha Siqueira Carvalho ◽  
Felipe Shindy Aiura ◽  
Auriclécia Lopes de Oliveira Aiura ◽  
Camila Maida de Albuquerque Maranhão ◽  
...  
Keyword(s):  
Thermal Environment ◽  
Physiological Responses ◽  
Productive Performance ◽  
Free Range

<i>Using a fuzzy system to evaluate the welfare of piglets reared in an environment with solar heating systems</i>

2017 ◽  
Author(s):  
Fl�vio A. Damasceno ◽  
Carlos E. A. Oliveira ◽  
Lucas H. P. Abreu ◽  
Leonardo Schiassi ◽  
Jofran L. Oliveira
Keyword(s):  
Fuzzy System ◽  
Solar Heating ◽  
Heating Systems

The optimization of solar heating systems

Solar Energy ◽  
1981 ◽  
Vol 26 (4) ◽  
pp. 375-376 ◽  
Author(s):  
Paul R. Barnes
Keyword(s):  
Solar Heating ◽  
Heating Systems

Application of T-S Fuzzy Neural Network in the Assessment of River Ecosystem Health

2013 ◽  
Vol 726-731 ◽  
pp. 958-962 ◽  
Author(s):  
Zhen Chun Hao ◽  
Xiao Li Liu ◽  
Qin Ju
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Fuzzy System ◽  
Ecosystem Health ◽  
Fuzzy Neural Network ◽  
Evaluation Model ◽  
Fuzzy Model ◽  
River Ecosystem ◽  
Fuzzy Neural

Healthy river ecosystem has been acknowledged as the object of river management, which is crucial for the sustainable development of cities. Simple and practical evaluation methods with great precision are necessary for the evaluation of river ecosystem health. Fuzzy system has been widely used in evaluation and decision making for its simple reasoning and the adoption of experts knowledge. However, much artificial intervention decreases the precision. Neural network has a strong ability of self-leaning while it is not good at expressing rule-based knowledge. The T-S fuzzy neural network model combines the advantages of fuzzy system and neural network. In this paper, the T-S fuzzy neural network model was used to establish a river ecosystem health evaluation model. Results show that the combination of T-S fuzzy model and neural network eliminates the influences of subjective factors and improve the final precisions efficiently.

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