scholarly journals Optimization of National Rice Production with Fuzzy Logic using Mamdani Method

2021 ◽  
Vol 1 (1) ◽  
pp. 36-43
Author(s):  
Wawan Wawan ◽  
Mai Zuniati ◽  
Agus Setiawan
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Fuzzy Inference ◽  
Raw Materials ◽  
Rice Production ◽  
Production Costs ◽  
Price Stability ◽  
Distribution Costs ◽  
Materials Used ◽  
Inference Methods

The purpose of this article is to optimization of national rice production with fuzzy logic using Mamdani method. Based on the results of the study, it is known that four parameters need to be considered to maintain the price stability of necessities, namely production; availability; demand and distribution. Optimization of production by producers and optimization of the ordering of goods by distributors are important steps to maintain price stability for necessities. Optimization of production and ordering of staple goods will have a significant impact on the financial sector because it is closely related to the prediction of the number of raw materials used, production costs, storage costs, and also distribution costs of goods. One of the fuzzy inference methods that can be used for this optimization is the Mamdani method. To get the output on the application of the fuzzy logic of the Mamdani method, four stages are needed, formation of fuzzy sets; application of implication functions; composition of rules and defuzzification. Fuzzy logic Mamdani method can be used to predict the amount of national rice that must be produced. If it is known that the need is 21,908,784 tons of rice and the supply is 65,457,456 tons,  the amount of national rice that must be produced is 14,624,592 tons.

scholarly journals Materials and Applications for Low-Cost Ceramic Membranes

Membranes ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 105 ◽  
Author(s):  
Amanmyrat Abdullayev ◽  
Maged Bekheet ◽  
Dorian Hanaor ◽  
Aleksander Gurlo
Keyword(s):  
Water Treatment ◽  
Raw Materials ◽  
Low Cost ◽  
Temperature Stability ◽  
Ceramic Membranes ◽  
Production Costs ◽  
High Temperature Stability ◽  
Waste Products ◽  
Recent Developments ◽  
Materials Used

In water treatment applications, the use of ceramic membranes is associated with numerous advantages relative to polymer-based filtration systems. High-temperature stability, fouling resistance, and low maintenance requirements contribute to lower lifecycle costs in such systems. However, the high production costs of most commercially available ceramic membranes, stemming from raw materials and processing, are uneconomical for such systems in most water treatment applications. For this reason, there is a growing demand for new ceramic membranes based on low-cost raw materials and processes. The use of unrefined mineral feedstocks, clays, cement, sands, and ash as the basis for the fabrication of ceramic membranes offers a promising pathway towards the obtainment of effective filtration systems that can be economically implemented in large volumes. The design of effective ceramic filtration membranes based on low-cost raw materials and energy-efficient processes requires a balance of pore structure, mass flow, and robustness, all of which are highly dependent on the composition of materials used, the inclusion of various pore-forming and binding additives, and the thermal treatments to which membranes are subjected. In this review, we present recent developments in materials and processes for the fabrication of low-cost membranes from unrefined raw materials, including clays, zeolites, apatite, waste products, including fly ash and rice husk ash, and cement. We examine multiple aspects of materials design and address the challenges relating to their further development.

scholarly journals Issues of Estimating the Quality of the Facilities Management of the Emercom of Russia at the Elimination of the Emergency Situations Consequences

2018 ◽  
Vol 7 (4.38) ◽  
pp. 704
Author(s):  
Valeriy Borisovich Vilkov ◽  
Andrey Kliment’evich Chernykh ◽  
Alexander Alekseevich Tarantsev ◽  
Yuri Evgenievich Aktersky ◽  
Ilya Danilovich Cheshko
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Fuzzy Inference ◽  
Facilities Management ◽  
Inference Algorithm ◽  
Emergency Situations ◽  
The Russian Federation ◽  
Civil Defence ◽  
Sets Theory

The article deals with the problem of multiobjective optimization with regard to the decision making on the use of the forces and facilities of the EMERCOM of Russia (Ministry of the Russian Federation for Affairs for Civil Defence, Emergencies and Elimination of Consequences of Natural Disasters). The purpose of the article is to create a method for prompt and reasonable calculations when making a decision on the use of the EMERCOM forces and facilities to eliminate the consequences of emergency situations. The proposed method uses fuzzy sets, fuzzy logic, and the Mamdani fuzzy inference algorithm. The work gives a substantial example illustrating the application of the mentioned theory to solve the problem of choosing the optimal version of the task performed by the facilities of the EMERCOM of Russia. Regarding the novelty, it should be noted that the quality characteristics of the solutions are fuzzy and not unambiguously defined, and therefore allow applying the effective mathematical apparatus of fuzzy sets theory, fuzzy logic and the Mamdani fuzzy inference algorithm in solving this problem. 

scholarly journals PREDIKSI HASIL PANEN PADI KABUPATEN & KOTA DI PROPINSI NUSA TENGGARA TIMUR DENGAN FUZZY INFERENCE SYSTEM (FIS)

2018 ◽  
Vol 10 (1) ◽  
pp. 42-48
Author(s):  
Yampi R. Kaesmetan
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Inference System ◽  
Agricultural Sector ◽  
Crop Yields ◽  
Fuzzy Inference ◽  
Rice Production ◽  
Percentage Error ◽  
Centroid Method ◽  
Inference System ◽  
Rice Yields

Rice (Oryza sativa) is a staple food source for the people of Indonesia. Most of the rice consumed is the result of national rice productivity. Often the government has difficulty in estimating the adequacy of basic food items that can be provided by domestic agriculture. Therefore a method is needed to predict rice yields accurately and precisely. The agricultural sector in East Nusa Tenggara is not a flagship of the community's economic activities. This is due to the geographical conditions of NTT which are less supportive for business activities in the agricultural sector. Even so, the prediction of agricultural products, especially rice yields, is needed to be predicted so that a forecast can be obtained in determining rice yields in 2017.  Fuzzy logic method in this case Fuzzy Inference System (FIS) is widely applied for forecasting or prediction. Fuzzy logic has a slowness in predicting crop yields for the following year based on crop yields in the previous year and information taken from the fuzzy information provided. Fuzzyinformation can be made a rule or rule as a consideration in predicting yields. By using the formula of Mean Absolute Percentage Error (MAPE) or Average Absolute Error, from the Fuzzy Mamdani model The Fuzzy Inference System (FIS) with the Mamdani model that has been built can be used to estimate the amount of rice production in the City District in NTT with the truth value reaching 97.8%. To determine the amount of rice production in 2017, the data is processed by using the help of the Matlab 2012 fuzzy toolbox software using the centroid method for defuzzification.

scholarly journals Potential possibilities of 3D printing for producing composite materials based on natural bioand synthetic polymers (a review)

2021 ◽  
Vol 25 ◽  
pp. 111-118
Author(s):  
D.G. Cheremisin ◽  
◽  
V.R. Mkrtchan ◽  
A.N. Ivankin ◽  
A.V. Ustyugov ◽  
...  
Keyword(s):  
Composite Materials ◽  
3D Printing ◽  
Raw Materials ◽  
Physical And Mechanical Properties ◽  
Synthetic Polymers ◽  
Production Costs ◽  
Specific Product ◽  
Wood Processing ◽  
Materials Used ◽  
Natural And Synthetic

A review is presented on the modern method of 3D printing of various composites based on synthetic and natural biopolymers with the inclusion of wood raw materials. Some features of scientific and technological approaches to the formation of a specific product using abstract computer modeling are described. A classification and review of the most common and promising 3D printing technologies using degraded raw materials with the inclusion of wood processing products is given. It is shown that using 3D printing, it is very promising to obtain «artificial wood», which is a mixture of a wood base with an inert polymer binder, which can be either based on synthetic polymers or based on natural biomatrix obtained from ecologically safe constituents of herbal raw materials. It is indicated that an important aspect of the problem of obtaining modern biocomposites is the dispersion of the materials used, which affects the entire complex of physical and mechanical properties of the product. The areas of application of the materials used are given. Trends in the development of 3D printing technology with the use of polymer binders based on natural and synthetic polymers are analyzed and the prospects of using natural biopolymers based on plant raw materials for the production of goods and materials necessary for humans as environmentally friendly products are shown. It is concluded that an impending explosive growth in the production and use of 3D composite materials based on natural and synthetic polymers with the inclusion of cheap wood components in the context of a significant reduction in production costs and the rapid production of the required products with low cost of products in the implementation of a highly efficient method 3D printing.

Comparison of Economic Efficiency of Rapeseed Production in Farms with Varied Fertilization Variants

2016 ◽  
Vol 20 (2) ◽  
pp. 63-70
Author(s):  
Tomasz K. Dobek ◽  
Paweł Kołosowski
Keyword(s):  
Economic Efficiency ◽  
Raw Materials ◽  
Production Costs ◽  
Mineral Fertilizers ◽  
Organic Fertilization ◽  
Mineral Fertilization ◽  
Rapeseed Production ◽  
Winter Rapeseed ◽  
Materials Used ◽  
Intensive Breeding

AbstractIntensive breeding is related to formation of considerable amount of manure which may be used as a natural fertilizer. Manure fertilization may cause reduction of the amount of applied mineral fertilizers and thus reduction of production costs. It may particularly relate to the species with great fertilization requirements such as winter rapeseed. The objective of the research was to compare economic efficiency of rapeseed production in two farms which use different fertilization variants. In one, only mineral fertilizers were used and in the second one – mineral fertilization was supplemented with manure organic fertilization. The use of manure caused reduction of expenditures on materials and raw materials used in production, in particular of fertilizers. At comparable yields obtained by two farms, technology based on manure fertilization proved to be more efficient.

Some Recent Defuzzification Methods

2017 ◽  
pp. 31-48 ◽  
Author(s):  
Harendra Kumar
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Fuzzy Number ◽  
Fuzzy Inference ◽  
Fuzzy Logic System ◽  
Single Number ◽  
Logic System

Defuzzification is a process that converts a fuzzy set or fuzzy number into a crisp value or number. Defuzzification is used in fuzzy modeling and in fuzzy control system to convert the fuzzy outputs from the systems to crisp values. This process is necessary because all fuzzy sets inferred by fuzzy inference in the fuzzy rules must be aggregated to produce one single number as the output of the fuzzy model.There are numerous techniques for defuzzifying a fuzzy set; some of the more popular techniques are included in fuzzy logic system. In the present chapter some recent defuzzification methods used in the literature are discussed with examples.

Some Recent Defuzzification Methods

Fuzzy Systems ◽  
2017 ◽  
pp. 1003-1019
Author(s):  
Harendra Kumar
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Control ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Fuzzy Number ◽  
Fuzzy Inference ◽  
Fuzzy Logic System ◽  
Single Number ◽  
Logic System

Defuzzification is a process that converts a fuzzy set or fuzzy number into a crisp value or number. Defuzzification is used in fuzzy modeling and in fuzzy control system to convert the fuzzy outputs from the systems to crisp values. This process is necessary because all fuzzy sets inferred by fuzzy inference in the fuzzy rules must be aggregated to produce one single number as the output of the fuzzy model.There are numerous techniques for defuzzifying a fuzzy set; some of the more popular techniques are included in fuzzy logic system. In the present chapter some recent defuzzification methods used in the literature are discussed with examples.

scholarly journals Establishing a New Link between Fuzzy Logic, Neuroscience, and Quantum Mechanics through Bayesian Probability: Perspectives in Artificial Intelligence and Unconventional Computing

Molecules ◽  
2021 ◽  
Vol 26 (19) ◽  
pp. 5987
Author(s):  
Pier Luigi Gentili
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Quantum Mechanics ◽  
Fuzzy Sets ◽  
Fuzzy Inference ◽  
Human Interaction ◽  
Cognitive Domain ◽  
Bayesian Probability ◽  
Total Probability ◽  
Unconventional Computing

Human interaction with the world is dominated by uncertainty. Probability theory is a valuable tool to face such uncertainty. According to the Bayesian definition, probabilities are personal beliefs. Experimental evidence supports the notion that human behavior is highly consistent with Bayesian probabilistic inference in both the sensory and motor and cognitive domain. All the higher-level psychophysical functions of our brain are believed to take the activities of interconnected and distributed networks of neurons in the neocortex as their physiological substrate. Neurons in the neocortex are organized in cortical columns that behave as fuzzy sets. Fuzzy sets theory has embraced uncertainty modeling when membership functions have been reinterpreted as possibility distributions. The terms of Bayes’ formula are conceivable as fuzzy sets and Bayes’ inference becomes a fuzzy inference. According to the QBism, quantum probabilities are also Bayesian. They are logical constructs rather than physical realities. It derives that the Born rule is nothing but a kind of Quantum Law of Total Probability. Wavefunctions and measurement operators are viewed epistemically. Both of them are similar to fuzzy sets. The new link that is established between fuzzy logic, neuroscience, and quantum mechanics through Bayesian probability could spark new ideas for the development of artificial intelligence and unconventional computing.

scholarly journals MODELLING OF TIME, COST AND RISK OF CONSTRUCTION WITH USING FUZZY LOGIC

2021 ◽  
Vol 27 (6) ◽  
pp. 412-426
Author(s):  
Edyta Plebankiewicz ◽  
Krzysztof Zima ◽  
Damian Wieczorek
Keyword(s):  
Risk Factors ◽  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Fuzzy Inference ◽  
Cost Calculation ◽  
Time Cost ◽  
Investment Process ◽  
The Cost ◽  
Available Information ◽  
Construction Schedule

The paper presents an overview of the literature from recent years devoted to planning the time, costs and risk of a construction investment using fuzzy logic. It also presents three own original models concerning the issue. The first model is used to build a fuzzy construction schedule taking into account fuzzy norms and the number of workers. The costing model uses fuzzy inference from CBR cases. The aim was to increase the accuracy and correctness of the cost calculation performed for the investor in the construction and investment process with a certain degree of vagueness of the available information about materials. In the last of the presented models, fuzzy sets were used to assess the effects of technological and construction (implementation) risk factors. The presented examples prove the usefulness of fuzzy logic in solving problems in construction, where we have incomplete and imprecise information.

scholarly journals Fuzzy Model for Risk Assessment of Machinery Failures

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 525 ◽  
Author(s):  
Dejan V. Petrović ◽  
Miloš Tanasijević ◽  
Saša Stojadinović ◽  
Jelena Ivaz ◽  
Pavle Stojković
Keyword(s):  
Risk Assessment ◽  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Fuzzy Inference ◽  
Mining Industry ◽  
Fuzzy Model ◽  
Assessment Model ◽  
Risk Level ◽  
Engineering System ◽  
Risk Assessment Model

The main goal of this research was the development of an algorithm for the implementation of negative risk parameters in a synthesis model for a risk level assessment for a specific machine used in the mining industry. Fuzzy sets and fuzzy logic theory, in combination with statistical methods, were applied to analyze the time picture state of the observed machine. Fuzzy logic is presented through fuzzy proposition and a fuzzy composition module. Using these tools, the symmetric position of the fuzzy sets with regard to class was used, and the symmetric fuzzy inference approach was used in an outcome calculation. The main benefit of the proposed model is being able to use numerical and linguistic data in a risk assessment model. The proposed risk assessment model, using fuzzy logic conclusions and min–max composition, was used on a mobile crushing machine. The results indicated that the risk level of the mobile crushing machine was in the “high” category, which means that it is necessary to introduce maintenance policies based on this high risk. The proposed risk assessment model is useful for any engineering system.

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