scholarly journals The Sunn [Eurygaster spp. (Hemiptera: Scutelleridae)] damage in wheat and the effect of seed amount used on yield by fuzzy logic method

2021 ◽  
Vol 11 (1) ◽  
pp. 239-246
Author(s):  
Mustafa Ilcin ◽  
Senol Celik
Keyword(s):  
Fuzzy Logic ◽  
Membership Function ◽  
Fuzzy Inference ◽  
Wheat Yield ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Sunn Pest ◽  
Herbal Products ◽  
Fuzzy Inference Mechanism ◽  
Triangular Membership Function

Sunn pest (Eurygaster spp.) is a highly harmful insect species for Wheatgrass. Especially with the emphasis it makes in herbal products, it causes the wheat to lose both its bread and pasta qualities. This study presents an example of a model that approximates the wheat yield in the irrigated field in Batman province according to the criteria selected through fuzzy logic. In the modelling, firstly the parameters affecting the wheat yield were determined and input and output variables were defined. In the next step, the membership functions are determined by doing the blurring process. The triangular membership function has been selected for the membership function. Later, fuzzy rule base was determined and fuzzy rules were formed. In the next step, the fuzzy inference mechanism was created. For the rinsing process, the "weight average" method was used. In the study, fuzzy logic toolbox was used in Matlab and the results obtained were seen to be useful in determining wheat yield per decare.

scholarly journals Rain Prediction using Fuzzy Logic

2019 ◽  
Vol 9 (1) ◽  
pp. 2796-2799
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Unit Commitment ◽  
Load Forecasting ◽  
Fuzzy Rule ◽  
Conventional Technique ◽  
Rule Base ◽  
Spinning Reserve ◽  
Generation Cost ◽  
Triangular Membership Function

Power system energy management system is observed as the breakthrough element for load forecasting. Load forecasting is advantageous so as to reduce the generation cost, spinning reserve capacity and increase the reliability of power system. The unit commitment, economic allotment of generation preservation schedule is crucial for short term load forecasting (STLF). In the current times, many techniques are being utilized for load forecasting, but Artificial Intelligence Technique (Fuzzy Logic and ANN) provides improved efficiency as in contrast with conventional technique (Regression and Time Series). In this particular paper, the author main purpose is to reduce flood conditions and drought. The main focus of the author is in the prediction of rainfall with the help of wind variation and temperature, speed. The paper represents a technique of STLF using fuzzy logic. Using Mamdani implication the fuzzy rule base is prepared. The software used for this is Matlab Simulink and fuzzy tool box. By using triangular membership function the forecasted results are obtained.

scholarly journals Line Follower Robot Optimization based Fuzzy Logic Controller Using Membership Function Tuning

2018 ◽  
Vol 7 (2.2) ◽  
pp. 112
Author(s):  
Supriadi Supriadi ◽  
Ansar Rizal ◽  
Didi Susilo Budi Utomo ◽  
Agusma Wajiansyah
Keyword(s):  
Fuzzy Logic ◽  
Membership Function ◽  
Fuzzy Logic Controller ◽  
Pulse Width Modulation ◽  
Fuzzy Inference ◽  
Inference System ◽  
On Line ◽  
Input Variables ◽  
The Right ◽  
Triangular Membership Function

The study was aimed to measure the performance of Fuzzy Logic Controller (FLC) on Line Follower Robot (LFR). FLC output is a deviation value of Pulse Width Modulation (PWM) to determine the rotational speed of the left and the right wheel. As input variables are current and previous line sensors. Tuning was applied to input and output variables in each membership function (MF) to conduct the best performance. This study used triangular membership function that consists of three MF. Mamdani Fuzzy Inference System (FIS) is used using nine rules. The result obtains that after MF tuning, the performance of the LFR settling time is 0.63s faster compare to that without tuning.  

Enhanced Fuzzy Assessment Methodology to Find Overlapping in Membership Function Using K Ratio to Find the Yield of Rice

2020 ◽  
pp. 155-174
Author(s):  
M. Kalpana ◽  
A. V. Senthil Kumar
Keyword(s):  
Fuzzy Logic ◽  
Expert Systems ◽  
Membership Function ◽  
Disease Incidence ◽  
Assessment Methodology ◽  
Fuzzy Expert Systems ◽  
Fuzzy Assessment ◽  
Triangular Membership Function ◽  
1000 Grain Weight ◽  
Hill Number

Fuzzy expert systems are designed based on fuzzy logic and deal with fuzzy sets. Many fuzzy expert systems have been developed for diagnosis. Fuzzy expert systems are developed using fuzzification interface, enhanced fuzzy assessment methodology, and defuzzification interface. Fuzzification helps to convert crisp values into fuzzy values. By applying the enhanced fuzzy assessment methodology for rice, the yield parameters of rice can be diagnosed with number of tillers per hill, number of grains per panicle, and 1000 grain weight. Pest and disease incidence becomes simple for scientists. Enhanced fuzzy assessment methodology for rice uses triangular membership function with Mamdani's inference and K Ratio. Defuzzification interface is adopted to convert the fuzzy values into crisp values. Performance of the system can be evaluated using the accuracy level. Accuracy is the proportion of the total number of predictions that are correct. The proposed algorithm was implemented using MATLAB fuzzy logic tool box to construct fuzzy expert system for rice.

Enhancing Fuzzy Inference System-Based Criterion-Referenced Assessment with a Similarity Reasoning Technique

2012 ◽  
pp. 302-327
Author(s):  
Tze Ling Jee ◽  
Kai Meng Tay ◽  
Chee Khoon Ng
Keyword(s):  
Fuzzy Inference System ◽  
Analogical Reasoning ◽  
Fuzzy Inference ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Large Set ◽  
Inference System ◽  
Similarity Reasoning ◽  
Criterion Referenced ◽  
Reasoning Technique

A search in the literature reveals that the use of fuzzy inference system (FIS) in criterion-referenced assessment (CRA) is not new. However, literature describing how an FIS-based CRA can be implemented in practice is scarce. Besides, for an FIS-based CRA, a large set of fuzzy rules is required and it is a rigorous work in obtaining a full set of rules. The aim of this chapter is to propose an FIS-based CRA procedure that incorporated with a rule selection and a similarity reasoning technique, i.e., analogical reasoning (AR) technique, as a solution for this problem. AR considers an antecedent with an unknown consequent as an observation, and it deduces a conclusion (as a prediction of the consequent) for the observation based on the incomplete fuzzy rule base. A case study conducted in Universiti Malaysia Sarawak is further reported.

scholarly journals Design of Indoor Room Gas CO and SO2 Detection Based on Microcontroller Using Fuzzy Logic

2019 ◽  
Vol 125 ◽  
pp. 23013
Author(s):  
Slamet Widodo ◽  
M.Miftakhul Amin ◽  
Ahyar Supani
Keyword(s):  
Carbon Monoxide ◽  
Fuzzy Logic ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Motor Speed ◽  
Fuzzy Rule Base ◽  
A Value ◽  
Base Logic ◽  
So2 Gas ◽  
Co Gas

The incidence of poisoning due to carbon monoxide gas arising from drilling activities on the first floor of a building in the Kelapa Gading beauty clinic in Jakarta resulted in 17 people experiencing poisoning. In this study developing a device on the sensor used to detect CO and SO2 gas, in the air of a closed room using gas sensor MQ 135 and MQ 136. The results of testing the CO and SO2 gas gauges using samples of cigarette smoke and sulfur powder using MQ 135 and MQ 136 sensors with fuzzy rule base logic for motor speed to produce CO and SO2 gas, that obtained a value of 0.233 ppm SO2 gas safe conditions and gas input CO with the sensor obtained a value of 0.513 ppm, the condition is safe so that the output is 49.8 ppm, the condition of the fan blower does not rotate. Whereas when the reading value of 5.0 ppm is very concentrated and the CO gas input with the sensor is 13.8 ppm the condition is very concentrated producing an output of 228 ppm the very danger.

Fuzzy Rule Interpolation

2011 ◽  
pp. 728-733 ◽  
Author(s):  
Szilveszter Kovács
Keyword(s):  
Fuzzy Inference ◽  
Fuzzy Rule ◽  
Fuzzy Reasoning ◽  
Fuzzy Relation ◽  
Rule Base ◽  
Rule Based ◽  
Fuzzy Rule Base ◽  
Current Observation ◽  
Rule Bases ◽  
Takagi Sugeno

The “fuzzy dot” (or fuzzy relation) representation of fuzzy rules in fuzzy rule based systems, in case of classical fuzzy reasoning methods (e.g. the Zadeh-Mamdani- Larsen Compositional Rule of Inference (CRI) (Zadeh, 1973) (Mamdani, 1975) (Larsen, 1980) or the Takagi - Sugeno fuzzy inference (Sugeno, 1985) (Takagi & Sugeno, 1985)), are assuming the completeness of the fuzzy rule base. If there are some rules missing i.e. the rule base is “sparse”, observations may exist which hit no rule in the rule base and therefore no conclusion can be obtained. One way of handling the “fuzzy dot” knowledge representation in case of sparse fuzzy rule bases is the application of the Fuzzy Rule Interpolation (FRI) methods, where the derivable rules are deliberately missing. Since FRI methods can provide reasonable (interpolated) conclusions even if none of the existing rules fires under the current observation. From the beginning of 1990s numerous FRI methods have been proposed. The main goal of this article is to give a brief but comprehensive introduction to the existing FRI methods.

Fuzzy logic approach for investigation of microstructure and mechanical properties of Sn96.5-Ag3.0-Cu0.5 lead free solder alloy

2017 ◽  
Vol 29 (4) ◽  
pp. 191-198 ◽  
Author(s):  
Muhammad Aamir ◽  
Izhar Izhar ◽  
Muhammad Waqas ◽  
Muhammad Iqbal ◽  
Muhammad Imran Hanif ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Fuzzy Logic ◽  
Solder Alloy ◽  
Thermal Aging ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Content Type ◽  
Wide Range ◽  
Fuzzy Logic Approach ◽  
Free Solder

Purpose This paper aims to develop a fuzzy logic-based algorithm to predict the intermetallic compound (IMC) size and mechanical properties of soldering material, Sn96.5-Ag3.0-Cu0.5 (SAC305) alloy, at different levels of temperature. The reliability of solder joint in materials selection is critical in terms of temperature, mechanical properties and environmental aspects. Owing to a wide range of soldering materials available, the selection space finds a fuzzy characteristic. Design/methodology/approach The developed algorithm takes thermal aging temperature for SAC305 alloy as input and converts it into fuzzy domain. These fuzzified values are then subjected to a fuzzy rule base, where a set of rules determines the IMC size and mechanical properties, such as yield strength (YS) and ultimate tensile strength (UTS) of SAC305 alloy. The algorithm is successfully simulated for various input thermal aging temperatures. To analyze and validate the developed algorithm, an SAC305 lead (Pb)-free solder alloy is developed and thermally aged at 40, 60 and 100°C temperature. Findings The experimental results indicate an average IMCs size of 5.967 (in Pixels), 19.850 N/mm2 YS and 22.740 N/mm2 UTS for SAC305 alloy when thermally aged at an elevated temperature of 140°C. In comparison, the simulation results predicted 5.895 (in Pixels) average IMCs size, 19.875 N/mm2 YS and 22.480 N/mm2 UTS for SAC305 alloy at 140°C thermally aged temperature. Originality/value From the experimental and simulated results, it is evident that the fuzzy-based developed algorithm can be used effectively to predict the IMCs size and mechanical properties of SAC305 at various aging temperatures, for the first time.

Optimized Fuzzy Logic Control Strategy for Parallel Hybrid Electric Vehicle Based on Genetic Algorithm

2013 ◽  
Vol 274 ◽  
pp. 345-349 ◽  
Author(s):  
Mei Lan Zhou ◽  
Deng Ke Lu ◽  
Wei Min Li ◽  
Hui Feng Xu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Control Strategy ◽  
Fuzzy Logic Control ◽  
Hybrid Electric Vehicle ◽  
Fuzzy Rule ◽  
Rule Base ◽  
Membership Functions ◽  
Logic Control

For PHEV energy management, in this paper the author proposed an EMS is that based on the optimization of fuzzy logic control strategy. Because the membership functions of FLC and fuzzy rule base were obtained by the experience of experts or by designers through the experiment analysis, they could not make the FLC get the optimization results. Therefore, the author used genetic algorithm to optimize the membership functions of the FLC to further improve the vehicle performance. Finally, simulated and analyzed by using the electric vehicle software ADVISOR, the results indicated that the proposed strategy could easily control the engine and motor, ensured the balance between battery charge and discharge and as compared with electric assist control strategy, fuel consumption and exhaust emissions have also been reduced to less than 43.84%.

Prediction on Aging of Reconstitutive Clayey Marine Soils Using Fuzzy-Logic

2003 ◽  
Author(s):  
Jorge Sa´nchez Moreno ◽  
Edison Castro Prates de Lima ◽  
Gilberto Bruno Ellwanger
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Rule ◽  
Experimental Tests ◽  
Optimization Method ◽  
Soil Strength ◽  
Evolutionary Strategy ◽  
Rule Base ◽  
Engineering Practice ◽  
Aging Effects ◽  
Effective Normal Stress

This paper presents an application of the fuzzy logic theory for the prediction of the soil strength depth variation due to aging effects. The results of experimental tests with reconstituted clayey soils of the Bay of Campeche in Mexico were used for the fuzzy rule-based system training. The Evolutionary Strategy (ES) was employed as an optimization method for the learning of the Mamdani-type fuzzy rule base. Fuzzy logic provides an easy and transparent method for incorporating common-sense type reasoning. The fuzzy logic model is based on a decision (inference) process that can be better described on a linguistic level using rules with soft facts. In this manner the clay soil strength through the time could be fuzzily predicted as a function of the mean effective normal stress, the time of consolidation and the water content. Illustrative examples showed that the result of prediction seems to be acceptable in engineering practice.

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