scholarly journals Model of a Company Competitiveness Control by Means of Artificial Intelligence Tools

2021 ◽  
Vol 9 (2) ◽  
pp. 60-65
Keyword(s):  
Artificial Intelligence ◽  
Information System ◽  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Research Direction ◽  
Pricing Policy ◽  
Building Projects ◽  
A Company ◽  
Artificial Intelligence Systems

This article is devoted to the problem of introduction of artificial intelligence systems into the activity of building participants and other building projects stakeholders. An example of determination of a contractor inner potential by means of fuzzy sets is presented. It is recommended to contracting companies to accumulate information about the components of the competitiveness potential, specifically about: their activity diversification (concentration), resource efficiency (salesvolumetocompanyassetsquotient), pricing policy flexibility (level of discounts at tenders), business reputation level –business assurance level of a company (percentage of works executed and paid under the won tenders in the total value of the won tenders). A model of determination of the influence of the indicated parameters onto the portion of the won tenders in the total value of the submitted tenders, which is based on fuzzy logic, is offered. Creation of an information system, which is presented in the form of a database, which accumulates information during the whole lifecycle of a company, is the following research direction.

scholarly journals Penerapan metode fuzzy sugeno untuk prediksi persediaan bahan baku

2019 ◽  
Vol 9 (2) ◽  
pp. 12-20
Author(s):  
Julio Warmansyah ◽  
Dida Hilpiah
Keyword(s):  
Fuzzy Logic ◽  
Raw Materials ◽  
Mean Absolute Percentage Error ◽  
Raw Material ◽  
Percentage Error ◽  
Human Power ◽  
Absolute Percentage Error ◽  
Input Variables ◽  
A Company

 PT. Cahaya Boxindo Prasetya is a company engaged in the manufacture of carton boxes or boxes. The company's activities also include cutting and printing services using machinery and human power. The problem faced in this company is the difficulty of predicting the amount of inventory of raw materials that will be  included in the production. The remaining raw materials for production will be used as the final stock to get the minimum, the goal is to reduce excess stock Overcoming this problem, fuzzy logic is used to predict raw material inventories by focusing on the final stock. In this study using Fuzzy Sugeno, with three input variables, namely: initial inventory, purchase, production, while the output is the final stock. Determination of prediction results using defuzzification using the average concept of MAPE (Mean Absolute Percentage Error). The results obtained, using the Fuzzy Sugeno method can predict the inventory of raw materials with a MAPE value of 38%. 

scholarly journals Tingkat Kesulitan Dinamis Menggunakan Logika Fuzzy pada Game Musik Tradisional Jawa Tengah

2021 ◽  
Vol 5 (2) ◽  
pp. 56-64
Author(s):  
Kadhana Reya Wisinggya ◽  
Hanny Haryanto ◽  
T. Sutojo ◽  
Edy Mulyanto ◽  
Erlin Dolphina
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Digital Games ◽  
Way Of Thinking ◽  
Traditional Songs ◽  
The Given

The culture in Indonesia is very diverse, one of which is traditional songs. However, knowledge of traditional songs is still small. Digital Games can spread knowledge about traditional songs, one of which is Central Javanese traditional songs. However, the Game that is made still has static difficulties, so the Game cannot follow the player's ability, resulting in the player feeling bored and not wanting to continue the Game. To generate dynamic difficulties, methods in artificial intelligence can be applied to Games, one of which is Fuzzy. So in this study proposed the application of dynamic difficulties using Fuzzy Logic in music Games / Rhythm Games. Fuzzy Logic is built based on mathematical values and represents uncertainty, where this logic imitates the human way of thinking. Fuzzy Logic can convert crisp input values into fuzzy sets by performing fuzzification. After the input value is converted, the input will be entered into the set of rules provided. Each rule produces a different output. After the process is complete, the output value will be converted back to the crisp output value. Based on the research conducted, it is found that Fuzzy Logic can be applied to music Games where the Game can follow the player's ability based on the given rules.

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 Zadeh's Centenary

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Ioan DZITAC
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Soft Computing ◽  
Special Issue ◽  
Introductory Paper ◽  
And Control

This is the introductory paper in a special issue on fuzzy logic dedicated to the centenary of the birth of Lotfi A. Zadeh published by International Journal of Computers Communications & Control (IJCCC). In 1965, Lotfi A. Zadeh published in the journal „Information and Control” the article titled „Fuzzy sets”, which today reaches over 117 thousand citations. The total sum of citations for all his papers is above 253 thousand. Based on the notion of fuzzy sets, fuzzy logic and the concept of soft computing emerged, bringing extremely important implications to the field of Artificial Intelligence (AI). In 2017, I published, whith F.G. Filip and M.J. Manolescu, a 42-page long paper in the IJCCC about the life and masterwork of Lotfi A. Zadeh, from which I will use some information in this material [15].

scholarly journals Fuzzy Logic Is Not Fuzzy: World-renowned Computer Scientist Lotfi A. Zadeh

2017 ◽  
Vol 12 (6) ◽  
pp. 748 ◽  
Author(s):  
Ioan Dzitac ◽  
Florin Gheorghe Filip ◽  
Misu-Jan Manolescu
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Fuzzy Sets ◽  
Soft Computing ◽  
50Th Anniversary ◽  
Fuzzy Sets Theory ◽  
Early Influence ◽  
Fuzzy Logic Theory ◽  
General Aspects ◽  
Sets Theory

In 1965 Lotfi A. Zadeh published "Fuzzy Sets", his pioneering and controversialpaper, that now reaches almost 100,000 citations. All Zadeh’s papers were citedover 185,000 times. Starting from the ideas presented in that paper, Zadeh foundedlater the Fuzzy Logic theory, that proved to have useful applications, from consumerto industrial intelligent products. We are presenting general aspects of Zadeh’s contributionsto the development of Soft Computing(SC) and Artificial Intelligence(AI),and also his important and early influence in the world and in Romania. Severalearly contributions in fuzzy sets theory were published by Romanian scientists, suchas: Grigore C. Moisil (1968), Constantin V. Negoita & Dan A. Ralescu (1974), DanButnariu (1978). In this review we refer the papers published in "From Natural Languageto Soft Computing: New Paradigms in Artificial Intelligence" (2008, Eds.: L.A.Zadeh, D. Tufis, F.G. Filip, I. Dzitac), and also from the two special issues (SI) of theInternational Journal of Computers Communications & Control (IJCCC, founded in2006 by I. Dzitac, F.G. Filip & M.J. Manolescu; L.A. Zadeh joined in 2008 to editorialboard). In these two SI, dedicated to the 90th birthday of Lotfi A. Zadeh (2011), andto the 50th anniversary of "Fuzzy Sets" (2015), were published some papers authoredby scientists from Algeria, Belgium, Canada, Chile, China, Hungary, Greece, Germany,Japan, Lithuania, Mexico, Pakistan, Romania, Saudi Arabia, Serbia, Spain,Taiwan, UK and USA.

Information Systems on Hesitant Fuzzy Sets

Fuzzy Systems ◽  
2017 ◽  
pp. 1425-1452
Author(s):  
Deepak D. ◽  
Sunil Jacob John
Keyword(s):  
Artificial Intelligence ◽  
Information System ◽  
Information Systems ◽  
Fuzzy Sets ◽  
Knowledge Extraction ◽  
The Other ◽  
Hesitant Fuzzy Sets ◽  
Power Set ◽  
Other Information ◽  
Membership Value

Knowledge extraction from information systems is one of the most significant problems in artificial intelligence. This paper attempts to study information systems in the hesitant fuzzy domain. It studies information systems which has a set of possible membership values. Illustration of a case is provided where the hesitant membership values are arrived at from attribute values whose membership values are a family of sets. The membership value here would turn out to be a subset of the power set of membership values from the usual information system. Although it does not mean that it is arrived at from usual information systems. Reduct, core, relative reduct, relative core and the corresponding indiscernibility matrices are also studied. Apart from these, paper also discusses the homomorphisms between hesitant information systems. For two homomorphic information systems the reduct and core of one information system are the corresponding images of the reduct and core of the other information system under this homomorphism.

scholarly journals Application of an Improved Formal Model of the Hybrid Development of Ontologies in Complex Information Systems

2020 ◽  
Vol 10 (19) ◽  
pp. 6777
Author(s):  
Yousef Ibrahim Daradkeh ◽  
Iryna Tvoroshenko
Keyword(s):  
Artificial Intelligence ◽  
Formal Model ◽  
Random Access ◽  
Heterogeneous Data ◽  
Subject Area ◽  
Alternative Representation ◽  
Complex Information ◽  
Hybrid Development ◽  
Artificial Intelligence Systems

Ontologies in artificial intelligence systems are an effective way to represent and integrate knowledge and data. The property of such structures is that any subject area is accurately described in formal language. There is a problem in the research and determination of the adequacy of ontologies under development. The perspective directions are model construction for the development of fuzzy ontologies and also the creation of methods for evaluating adequacy. The achieved results allow one to implement the processes of supporting the development and integration of ontologies of complex systems on the basis of intelligent approaches. The method is proposed to solve the problem of alternative representation and the integration of knowledge and data in artificial intelligence systems. The methodology of improving the model of the hybrid development of fuzzy ontologies is described here; it provides the preliminary modification of models of extensive and intensive progress of ontologies in space and time. The identified features of fuzzy ontology processing allow us to create a procedure for finding and eliminating inadequacies. The software implementation of the application for the integration and presentation of heterogeneous data is carried out. The consumption of Random Access Memory (RAM) for the proposed models is analyzed. The further perspectives of the proposed research are determined in accordance with the principles of classification.

scholarly journals Penjemur Kerupuk Otomatis Menggunakan Sistem Kecerdasan Buatan Arduino Uno Dengan Menerapkan Metode Fuzzy Logic Controller (FLC)

2020 ◽  
Vol 7 (2) ◽  
pp. 235
Author(s):  
Risal Suandi
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic Controller ◽  
Drying Process ◽  
Artificial Intelligence System ◽  
The Road ◽  
Intelligence System ◽  
Arduino Uno ◽  
On The Road ◽  
A Company ◽  
Artificial Intelligence Systems

Denang jangek cracker factory is a company located on the road denai Kota medan, this factory everyday produces jangek crackers, at the stage of production there is a stage of drying jangek crackers used manually, where crackers are placed outside the room exposed to the sun's heat at the drying stage . When the rainy season arrives this makes a lot of time taken up during the drying process because often it rains suddenly, then the crackers must be immediately put in or placed in a dry place not exposed to rain water. The FLC method is a method that is often used in making artificial intelligence systems that are applied to an Arduino uno microcontroller where the method only recognizes on or Off, 0 or 1, nothing is vague. From the description of the problem above, the writer makes an artificial intelligence system that is applied to a device, namely Arduino Uno, where the system thinks like humans, who can think like when it rains so that the tool will move or close crackers that are being dried in the sun so that it is not exposed to rain with using an FLC method applied to Arduino Uno

Information Systems on Hesitant Fuzzy Sets

2016 ◽  
Vol 3 (1) ◽  
pp. 71-97 ◽  
Author(s):  
Deepak D. ◽  
Sunil Jacob John
Keyword(s):  
Artificial Intelligence ◽  
Information System ◽  
Information Systems ◽  
Fuzzy Sets ◽  
Knowledge Extraction ◽  
The Other ◽  
Hesitant Fuzzy Sets ◽  
Power Set ◽  
Other Information ◽  
Membership Value

Knowledge extraction from information systems is one of the most significant problems in artificial intelligence. This paper attempts to study information systems in the hesitant fuzzy domain. It studies information systems which has a set of possible membership values. Illustration of a case is provided where the hesitant membership values are arrived at from attribute values whose membership values are a family of sets. The membership value here would turn out to be a subset of the power set of membership values from the usual information system. Although it does not mean that it is arrived at from usual information systems. Reduct, core, relative reduct, relative core and the corresponding indiscernibility matrices are also studied. Apart from these, paper also discusses the homomorphisms between hesitant information systems. For two homomorphic information systems the reduct and core of one information system are the corresponding images of the reduct and core of the other information system under this homomorphism.

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