Determination of winter and summer ventilation rates of a laying hen house using fuzzy logic method

Diseases diagnosis using fuzzy logic methods: A systematic and meta-analysis review

This paper presents the efficacy of a “tuned” fuzzy logic method at determining the height of the boundary layer using the measurements from a 1280 MHz lower atmospheric radar wind profiler located in Gadanki (13.5°N, 79°E, 375 mean sea level), India, and discusses the diurnal and seasonal variations of the measured convective boundary layer over this tropical station. The original fuzzy logic (FL) method estimates the height of the atmospheric boundary layer combining the information from the range‐corrected signal‐to‐noise ratio, the Doppler spectral width of the vertical velocity, and the vertical velocity itself, measured by the radar, through a series of thresholds and rules, which did not prove to be optimal for our radar system and geographical location. For this reason the algorithm was tuned to perform better on our data set. Atmospheric boundary layer heights obtained by this tuned FL method, the original FL method, and by a “standard method” (that only uses the information from the range‐corrected signal‐to‐noise ratio) are compared with those obtained from potential temperature profiles measured by collocated Global Positioning System Radio Sonde during years 2011 and 2013. The comparison shows that the tuned FL method is more accurate than the other methods. Maximum convective boundary layer heights are observed between ~14:00 and ~15:00 local time (LT = UTC + 5:30) for clear‐sky days. These daily maxima are found to be lower during winter and postmonsoon seasons and higher during premonsoon and monsoon seasons, due to net surface radiation and convective processes over this region being more intense during premonsoon and monsoon seasons and less intense in winter and postmonsoon seasons.

Determining the quality of eggs in general is used by placing eggs on a flashlight. The detection system is very necessary to determine good egg quality or rotten eggs, so that the conditions of the eggs can be known by the chicken farm company and then will be sold to the community. This egg detecting system utilizes several sensor devices that are combined. The sensor used to detect the quality of eggs is a light sensor and a heavy sensor by connected with a microcontroller. So that there is no ambiguity towards the decision making of good egg or rotten eggs, then processing the data is obtained from these sensors using Fuzzy Logic and Firebase methods in real time as data storage media, and actuators will distribute or separate good eggs or the rotten eggs one. With the development of technology now, we can use the Internet of Things (IoT) technology, one of the systems check the quality of eggs which are good or not good. This system is built using a microcontroller to coordinate the running of the system using the Fuzzy Logic Method that applies inside. Final information is obtained on the form of egg quality in real time. The test results were carried out using the Fuzzy Logic method and obtained 95% results from 20 eggs and had 1 wrong egg. When using system hardware without using the fuzzy logic method on the microcontroller that using only a light sensor and a heavy sensor it produces a result of 75% from 20 eggs and had 5 wrong eggs. Using the egg detection optimization method can be increased up to 20%.

Clustering is an effective strategy to minimize the energy consumption of nodes in energy-constrained wireless sensor networks. In clustered wireless sensor networks, the network is divided into multiple clusters, and each cluster has a coordinator called cluster head, which collects data from its cluster members and forwards it to the base station through other cluster heads. Cluster wireless sensor networks often have hot spot problems. Due to high energy consumption caused by data forwarding load, cluster heads near the base station die earlier. This kind of node death leads to the coverage loophole of the network early and reduces the life cycle of the network. Unequal clustering is a technology to solve this problem. In non-uniform clustering wireless sensor networks, the size of clusters near the base station is smaller than that far away from the base station. In the process of cluster formation, non-cluster-head nodes are generally added to nearby cluster-head nodes. In this paper, an unequal clustering protocol based on fuzzy logic and entropy weight method (FEUC) is proposed to extend the life cycle of the network. This protocol makes the network form clusters of different sizes. Fuzzy logic method is used to select cluster heads and non-cluster heads join cluster heads to form clusters. The objective entropy weight method is used to select relay cluster heads to implement multi-hop routing strategy. Mamdani method is used for fuzzy reasoning. The proposed protocol is compared with the low-energy adaptive clustering hierarchy (LEACH) protocol, the energy-aware unequal clustering fuzzy protocol (EAUCF), and the fuzzy-based unequal clustering protocol (FUCA), in all scenarios, the proposed protocol has better performance.

In This research, the fuzzy logic (FC) method was used to calculate the main parameters of photovoltaic cell. Some of the basic silicon solar cell parameters were measured in the laboratory. A fuzzy logic method is used to demonstrate and compared the value of the solar cell's parameters corresponding to I-V curve of this cell. The results showed that the fuzzy logic method is very suitable for comparing the optimal values of the photovoltaic cell parameters.

MRI definition of target volumes using fuzzy logic method for three-dimensional conformal radiation therapy

SUMMARY The housing system plays a critical role in welfare of laying hens, and various systems have been implemented throughout the world. Benefits vary for different housing schemes. Important considerations for welfare also include environmental conditions (air quality), but these parameters are not well documented for different laying hen housing systems. Regarding the consequences of poor air quality, it includes diminished production performance and impaired bird health. Therefore, the objective of this research was to assess the air quality in three housing system types for laying hens. One farm from each type (conventional cages, furnished cages and alternative system) was selected, based on farm access and availability. The evaluated environmental variables included: ammonia concentration, carbon dioxide concentration, air temperature, relative humidity, air flow velocity, bacteria and fungi. All parameters were determined using hygiene specific methods, in three different points, in three consecutive days in the summer. The temperature was adequate in all the hen houses, while the relative humidity was below the hygienic norms in the system with furnished cages. The air currents’ velocity was lower than is recommended by welfare standards, in all the assessed farms. The concentration of carbon dioxide was below the threshold limit in all three housing types, higher values being recorded in the alternative system (900 ppm). The ammonia concentration varied (5-25 ppm), being significantly (p<0.05) higher in the alternative system comparing with the conventional and furnished cage housing. The numbers of bacteria (4.49 x 10 6 CFU/m 3 ) and fungi (1.49 x 10 5 CFU/m 3 ) were significantly (p<0.05) higher in the alternative system, comparing with the other two systems. Significant differences (p<0.05) were also found between the conventional cages and the furnished ones for the total number of mesophilic bacteria (5.07 x 10 5 CFU/m 3 and 8.47 x 10 4 CFU/m 3 , respectively). The obtained values are conformable with the results of other studies (Matkovic et al., 2007; Nimmermark et al., 2009). The air quality problems are more frequently encountered in the systems where the birds are kept on the floors than in cage systems, especially in those hen houses where the ventilation rates are low, but these can also be significant in cage housing due to the hens’ manure. The results of the study indicate better air quality in the system with furnished cages comparing with the other two housing systems.

Comparison of performances of fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS) for estimating employee labor loss

Fuzzy logic and statistical-based modelling of the Marshall Stability of asphalt concrete under varying temperatures and exposure times

Four similar experimental poly-greenhouse models with different shading rations and ventilation gaps were used and compared with the open field condition. One of the four poly-greenhouse models was covered by a single layer of polyethylene (without shading), and the others three models were covered with an external black screen shade net sheets of 25%, 63% and 75% shading ratios, during the winter months. While, three poly-greenhouse models were covered only with black screen shade net sheets of 25%, 63% and 75% shading ratios during the summer months. The thermal performance of the greenhouse models and their effects on seedlings germination and yield of tomato (GSI Seed, Hybrid Tomato, Nora-765) were investigated under Fayoum depression climatic conditions during the winter and summer months of 2009. The obtained results indicated that the air temperature inside the un-shaded model was almost higher than in shaded models and ambient temperature during the winter months (January to May). The air temperature inside the greenhouse models covered only by black screen shade net sheets of 63% and 75% shading ratios were down the ambient temperature during the summer months (June to October) with ventilation rate during the night time. All shading ratios caused to increase the relative humidity inside the greenhouse models, especially with 63% and 75% shading ratios. As shading ratio increased the light intensity decreased, and thus, the light intensity was adequate when it decreased by 63% and 75%, which is satisfactory for seedlings germination, plant growth and yield of tomato at the summer months. Poly-greenhouse with single layer of polyethylene was found more suitable for seedlings germination, plant growth and yield of tomato than those with the other shading ratios and open field condition during the winter months. Poly-greenhouse covered only by black screen sheets (especially with 63% or 75% shading ratios) was found more suitable for better seedlings germination, plant growth and yield of tomato than this with 25% shading ratio and open field condition in the summer months.

To increase the amount of export and marketability of walnuts, a quick, cheap and non-destructive sorting approach should be used. The overall objective is to sort the full, half full and empty walnuts relying on fuzzy logic and sound analysis methods. To sort the walnuts the sound processing technique was used. In this regard, effective parameters on sorting and quality such as: size and shape of walnut were studied. For this purpose, 300 dried walnuts were randomly selected from a walnut orchard for use in experiments. An electronic system consisting of a computer, a microphone, and a mechanical section consisting of a sound chamber were designed to measure the sound intensity of a walnut. At this stage, each walnut was released in three directions: back, side and abdomen 30 cm above the surface of the sound chamber. The sounds were recorded by a microphone with acoustic beats on a sound chamber made of wood and a 45-degree slope. The data from the sound signals were stored in the time domain on the computer and then processed by the MATLAB software. In order to eliminate the ambient noise of signals, Kalman filter algorithm was used to achieve high accuracy and fast convergence. Then these data were analyzed by fuzzy logic method. In this research, WEKA software and J48 algorithm have been used to classify walnuts based on their filling and using the features extracted from the walnut collision with a wooden plate. In order to classify walnuts according to the fullness of walnut kernels, a scientific and innovative index called Full Kernel Index (FK) was used. The results of this study showed that for classification of walnut, decision trees due to simplicity of structure and creation of fuzzy rules and threshold values of membership functions make fuzzy inference system with high accuracy. The final fuzzy model was presented to classify walnut into two classes with 0.087% separation accuracy and 3 classes with 0.080% separation accuracy.

The prediction of future behavior of this under study phenomenon is considered as the most important and vital subject in statistics. This study took a great deal of concern by statistics' researchers in order to estimate the parameters of time series' samples, consequently, using it in the prediction and controlling of areas for applicatory fields. Recently, many researches appeared to use modern computer technologies in analyzing nonlinear series, besides, many different statistical subjects, such as neural-networks and fuzzy logic. The purpose of this research is characterized by using fuzzy logic method and comparing it with Holt Winters additive method depending upon mean square error MSE to predict the chronological series' values. The fuzzy logic method had overcome the additive Holt Winters method according to the statistical norms. Therefore, the fuzzy method could be the best and the most accurate method in predicting the time series.

The application of the gripper in the industrial world has facilitated human work in the sorting process but has the disadvantage of not being able to sort objects based on the object's color. Conditions like these can affect the production quality factor when sorting objects. This research resulted in a gripper end effector system using the fuzzy method and the telegram application as a control, which has a function to distinguish the color of objects gripped by the gripper, thereby minimizing errors in sorting objects based on color. Telegram is used because the application is relatively light and can be accessed anywhere as long as it is connected to an internet connection. This study uses the fuzzy logic method as a decision-making process. The fuzzy method is used because it is very flexible and has a tolerance value in the existing data. The telegram function in this study is the main control to give orders to the gripper. The TCS3200 color sensor, in this study, is used to detect object color. The TCS3200 sensor converts the light intensity value to 8 bits so that the microcontroller can read it for each color in the test. The colors red, green, and blue were chosen as a reference because they are the primary or basic colors of all colors. From the results of testing the entire system in this study, 90% success was obtained in moving objects precisely based on the object's color. This result is enough to prove that the system can work properly.

Prediction of laying hen house odor concentrations using machine learning models based on small sample data

Bu çalışmada, yapay zekâ yöntemlerinden biri olan bulanık mantık yöntemi kullanılarak, çelik boru profillerin çekme ve basınç kuvveti etkisindeki kapasitelerini belirleyebilmek için iki adet bulanık model oluşturulmuştur. 2018 Türk Çelik yapılar Yönetmeliğinde belirtilen GKT yöntemine göre oluşturulan her iki bulanık modelde de, çelik sınıfı S355 olarak sabit olarak tutulurken, kesit çapı (D), profil et kalınlığı (t) ve eleman uzunluğu (L) değişken parametreler olarak dikkate alınmıştır. Eksenel çekme kapasitesi (Tn) ve eksenel basınç kapasitesi (Pn) ayrı ayrı olarak bu modellerin çıktı parametrelerini oluşturmuşlardır. Her iki modelin oluşturulmasında aynı girdi değişkenleri değerlerine sahip ancak çıktı parametreleri farklı olan 1400 ‘er adet örnek çözüm kullanılmıştır. Kullanılan bu örnek çözümlerin haricinde 988 ‘şer adet farklı örnek çözüm ile bu modeller test edilerek, sırasıyla maksimum % 2.764 ve maksimum % 4.076 hata ile eksenel çekme ve basınç dayanımlarının tahminde kullanılabilecekleri ortaya konulmuştur. Daha sonra geliştirilen bulanık modellere, bulanık ters mantık yöntemi 3 farklı izostatik düzlem kafes sistem örneği için uygulanarak bu kafes sistemleri oluşturan çubuk elemanların tasarımları gerçekleştirildikten sonra dayanım kontrolleri karşılaştırmalı olarak 2018 Türk Çelik yapılar Yönetmeliğinde belirtilen GKT yöntemi ile gerçekleştirilmiştir. Sonuç olarak, bulanık mantık ve bulanık ters mantık yöntemlerinin birlikte aynı sayısal veriyi kullanarak boru kesitli çelik kafes sistem elemanların kapasitelerinin belirlenmesinde ve aynı zamanda tasarımlarının gerçekleştirilmesinde model hataları da dikkate alınarak güvenle kullanılabilecekleri ortaya konulmuştur.