Fuzzy Logic

An approach for emulating quantum circuits using
conventional analog hardware is presented based on
the intuitive similarity between fuzzy logic and quantum
superposition, as well as some geometrical analogies.
This approach has the advantage of being easy
to implement on dedicated hardware for parallel processing
of membership functions and fuzzy inference,
compared to conventional quantum computing, which
requires quantum mechanical systems which are extremely
sensitive to noise and difficult to extend to
large scale systems. Using geometrical analogies and
a suitable transformation, qubits are modeled as pairs
of fuzzy membership functions evolving on the unit
square and basic one qubit gates are modeled as transformations
on this unit square. A fuzzy implementation
of the one bit and two bit Deutsch-Jozsa algorithm
is proposed. Physical implementation and advantages,
such as the possibility of implementing nonlinear or
non-unitary gates, as well as drawbacks of the proposed
model compared to conventional quantum computing
are shown.

7th International Conference on Artificial Intelligence and Applications (AI 2021) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its applications. The Conference
looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and
share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to.

9
th International Conference of Artificial Intelligence and Fuzzy Logic (AI & FL 2021)
provides a forum for researchers who address this issue and to present their work in a peerreviewed forum. Authors are solicited to contribute to the conference by submitting articles that
illustrate research results, projects, surveying works and industrial experiences that describe
significant advances in the following areas, but are not limited to these topics only.
Authors are solicited to contribute to this conference by submitting articles that illustrate
research results, projects, surveying works and industrial experiences that describe significant
advances in the areas of Artificial Intelligence & applications

The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications.

Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Artificial Intelligence & applications.

Lotfi A. Zadeh, in his article entitled “The Birth and Evolution of Fuzzy Logic” discusses R.E. Kalman’s and W. Kahan’s strong criticisms of fuzzy logic and presents his answers to these criticisms. The main subject of this debate consisted of a discussion of the criticisms targeting at the concept of the linguistic variable and, consequently, at fuzzy logic. The main aim of my paper is to expose the methods of the positive natural sciences which generally form the basis of these criticisms, to analyze and to evaluate scientific and epistemological theories of science historians and philosophers of science such as T.S. Kuhn and K.R. Popper, and to try to show the importance of fuzzy logic in this context. There is a huge amount of work to be done within the framework of the philosophy and sociology of science in order to provide some hints about the future of fuzzy logic, therefore it must be stated that this paper can only be considered as a modest contribution to this vast field.

The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications.

This paper aims to predict the hand values (HVs) and total hand values (THVs) of functional fabrics by applying the fuzzy logic model (FLM) and artificial neural network (ANN) model. Functional fabrics were evaluated by trained panels employing subjective evaluation scenarios. Firstly, the FLM was applied to predict the HV from finishing parameters; then, the FLM and ANN model were applied to predict the THV from the HV. The estimation of the FLM on the HV was efficient, as demonstrated by the root mean square error (RMSE) and relative mean percentage error (RMPE); low values were recorded, except those bipolar descriptors whose values are within the lowermost extreme values on the fuzzy model. However, the prediction performance of the FLM and ANN model on THV was effective, where RMSE values of ∼0.21 and ∼0.13 were obtained, respectively; both values were within the variations of the experiment. The RMPE values for both models were less than 10%, indicating that both models are ro...

This study presents the effects of environmental pollution on the quality of domestic roof-harvested rainwater (DRHRW) using fuzzy comprehensive assessment (FCA). Seven metals (Cu, Cd, Pb, Zn, Fe, Ca, and Mg) and six water-quality parameters (Acidity, PO4 (3-), SO4 (2-), NO3 (-) , Cl(-), and pH) were investigated in DRHRW sampled from 12 sampling points each from Ibadan (residential) and Lagos (industrial) environments, Nigeria. The results of these parameters were formulated into membership function fuzzy matrices based on four contamination classifications of high, marginal, low, and poor qualities using regulatory limits as criteria. The products membership function matrices and weight matrices generated indices that classified the degree of anthropogenic activity impact on the sites. Results of FCA classified the DRHRW from residential environment as between high and marginal quality, whereas DRHRW from industrial environment is classified between marginal and low quality. Lead ...

Three dimensional object extraction and recognition (OER) from LIDAR data has been an area of major interest in photogrammetry for quite a long time. However, most of the existing methods for automatic object extraction and recognition from LIDAR data are just based on the range information and employ parametric methods and object’s vagueness behaviour is basically neglected. Thus, these methods do not take into account the extraction and recognition complexities and may fail to reach a satisfied reliability level in complex situations. In this paper a novel approach based on the following strategies is formulated and implemented: (a) for a more comprehensive definition of the objects, information fusion concept is utilized, i.e., object’s descriptive components such as 3D structural and textural (ST) information are automatically extracted from first/last rang and intensity information of LIDAR data and simultaneously fed into the evaluation process, (b) for a more realistic expres...

In this paper, the implementation of a neural network-based fuzzy modeling approach to assess aspects of students' learning style in the discovery learning environment “Vectors in Physics and Mathematics” is presented. Fuzzy logic is used to provide a linguistic description of ...

The aim of this research was to develop an intelligent system for pasteurised milk quality assessment and prediction that could help the quality decision makers to assess and predict the pasteurised milk quality. Utilizing Expert System and Artificial Neural Network (ANN), which called SINKUAL-SP, did these analyses. The reasoning strategy used was “Forward Chaining” and the tracing method used was “Best First Search”. Certainty Factor (CF) was used for handling uncertainty. Multi-layer neural network architecture was used. The suited activation function was Sigmoid Bipolar, which gave the best performance network with learning rate 0.005 and momentum 0.9 together with RMSE, MSE and SSE as an error criterion. The validation for neural network indicated the conformity between the output of neural network and the goal output with RMSE value of 0.0099. The system was verified and validated by using real data collected from pasteurised milk and milk Products Company at West Java, Indone...

Fuzzy Logic has been proposed for information representation and manipulation in databases, being the current tendency to study mechanisms of flexible querying to traditional databases. SQLf has been one of the efforts in this tendency. On the other hand, there are many different dialects of SQL. There are two major standards: ANSI (American National Standards Institute) SQL and an updated

Minat generasi muda terhadap kebudayaan Wayang semakin menurun, padahal Wayang memiliki banyak manfaat dalam bidang pendidikan dan kebudayaan. Game adalah media interaktif yang dapat digunakan sebagai sarana untuk melestarikan Wayang. Penelitian ini menggunakan logika fuzzy sebagai pendekatan untuk implementasi tingkat kesulitan dinamis pada game. Parameter input diambil dari atribut karakter pemain saat bermain, kemudian sistem akan mengolah dan mengklasifikasi pemain yang nantinya akan berdampak pada tingkat kesulitan dalam game. Parameter yang digunakan adalah sisa lifepoint, sisa waktu, kemampuan menyelesaikan tugas, tingkat kesulitan sebelumnya, tingkat keakuratan tembakan pemain, serta banyaknya pemain melakukan percobaan. Hasil dari penelitian ini adalah sistem mampu memodelkan tingkat kemampuan pemain sehingga menghasilkan tingkat kesulitan yang dinamis sesuai dengan kemampuan pemain tersebut.

A fuzzy logic-based system has been applied to a number of cases in medicine especially in the area of the development of diagnostic systems and has been discovered to produce accurate results. In this paper, a fuzzy logic-based system is presented which is used to simulate a prediction model for determining the likelihood of Sickle Cell Anemia (SCA) in individuals given a 3-tuple record containing the level of fetal haemoglobin, genotype and the degree of Anemia. Knowledge was elicited from an expert at Federal Medical Centre, Owo, Ondo State, Nigeria and was used in developing the rule-base and simulated the prediction model using the MATLAB software. The results of the fuzzification and defuzzification of variables, inference engine definition and model testing was also presented and showed that the fuzzy logic based model will be very useful in the prediction of the likelihood of Sickle Cell Anemia (SCA) among Nigerian patients.

This paper shows a strategy suitable for navigating autonomous robots in a completely unknown environment. The method proposed combines optimum path planning techniques with fuzzy logic to avoid obstacles and to determine the shortest path towards its goal. The technique computes the potential surface using Dijkstra’s algorithm in a moving window, updating the cost map as it moves with the information obtained by the ultrasonic sensors. A Fuzzy Logic Controller (FLC) controls the wheels of a differential drive robot to the angle of minimum potential. This ensures a smooth trajectory towards the objective. A second FLC controls the average speed of the platform.

Classic and fuzzy logic and their usefulness in clinical diagnosis. The theory of probability is often considered a device to protect the classical two-valued logic from the evidence of its inadequacy to understand and show the complexity of world [1]. This can be true, but it is not possible to discard the theory of probability. I will argue that the problems and the application fields of the theory of probability are very different from those of fuzzy logic. After the introduction on the theoretical bases of fuzzy approach to logic, I have reported some diagnostic argumentations employing fuzzy logic. The state of normality and the state of disease often fight their battle on scalar quantities of biological values and it is not hard to establish a correspondence between the biological values and the percent values of fuzzy logic. Accordingly, I have suggested some applications of fuzzy logic in clinical diagnosis and in particular I have utilised a fuzzy curve to recognise subjects with diabetes mellitus, renal failure and liver disease. The comparison between classic and fuzzy logic findings seems to indicate that fuzzy logic is more adequate to study the development of biological events. In fact, fuzzy logic is useful when we have a lot of pieces of information and when we dispose to scalar quantities. In conclusion, increasingly the development of technology offers new instruments to measure pathological parameters through scalar quantities, thus it is reasonable to think that in the future fuzzy logic will be employed more in clinical diagnosis.

This paper describes the development of a generalized agent -based simulation tool for studying manpower and personnel management behaviors. The subject matter of the simulation are complex organizational behaviors found within Uni ted States Navy Manpower and Personnel processes. Behavior of such a complex system is typically associated with a hierarchi- cal structure in which the lowest level agents are

An upstream access scheme for Ethernet passive optical networks, called the intelligent fuzzy-logic-based dynamic bandwidth allocation algorithm (IFLDBA) has been proposed. The algorithm provides the allotment of bandwidth between optical network units (ONUs) and within ONUs. Fuzzy logic is used to improve the bandwidth allocation within each ONU. We compare the IFLDBA algorithm with the existing broadcast polling algorithm. The results show that IFLDBA has bandwidth utilization of up to 21% better and lower delay than the broadcast polling algorithm.

54 years + full time experience & over 64800 satisfied clients World Wide +27818084431

Are Any Of The Serious Problems Listed Below (Or Similar) Adversely Affecting You Or Your Loved Ones...And You Are Feeling 'Powerless' To Find A Solution?

*I BRING BACK LOST LOVERS IN 24hrs.

*REMOTE CONTROL OVER LOVERS.

*ALL TYPES OF SPELL CASTING & VOODOO WORKER.

* BLACK MAGIC EXPERT & CURSE REMOVER.

* GET LUCK FROM FORE FATHERS, BRING YOUR LOVED ONES CLOSER TO YOU, WE CHASE EVIL SPIRITS, WE DO HOME PROTECTIONS, FINANCIAL PROBLEMS.

* DELAYED PACKAGES, PENSION OR ACCIDENTAL FUNDS, COME NOW!!

* IS YOUR HEALER TAKING LONG TO SOLVE YOUR PROBLEMS? THIS IS YOUR CHANCE TO BE HELPED QUICKLY.

*GET RIDE OF ANY WITCHCRAFT, BAD LUCK & CURSES.

* EXPERT IN DISTANCE HEALING.

*COURT CASES EVEN IF ONE IS CONVICTED[IF THERE'S A CHANCE OF APPEALING]


*UNFINISHED JOBS BY OTHER DOCTORS-IF NOT SATISFIED-COME TO ME.

*ARE YOU BEING FORCED INTO A DIVORCE?


*HEALERS WHO NEEDS MORE POWERS TO HEAL THEIR


* DO YOU WANT TO HAVE CHILDREN OF YOUR CHOICE?

*DO YOU WANT QUICK MARRIAGE PROPOSAL?


*HIRE SHORT BOYS TO GIVE YOU RICHNESS IN 1 WEEK.$3800

*BUY AMAYEMBE [ANCESTRAL SPIRITS] TO MAKE YOU RICH.$4500

AND MANY MORE.....CALL: +27818084431 OR VISIThttp://drpinkietraditionalhealer.wordpress.com
Email:drpinkie1@gmail.com
http://drpinkietraditionalhealer.wordpress.com
website : drpinkie.co.za

Don't quit, Winners don't quit and quitters don't win! "If any of the issues above resonate with you and you have nowhere else to turn I can help you no matter where you are - anywhere in the World. All work is guaranteed to be 100% remote, and 100% discreet.

I have well over 54 years full time professional international experience, successfully healing the problems above (and more) for people like you... when absolutely nothing else would work."
website : drpinkie.co.za

""Origin–destination (O–D) matrix estimation methods based on traffic counts have been largely discussed and investigated. The most used methods are based on Generalised Least Square estimators (GLS) that use as input data a starting O–D matrix and a set of traffic counts. In addition to traffic counts, the analysts could know other general information about travel demand or link flows, based on their experience, or spot data, but few works deal with the matter of including effectively these sources of information.

This paper proposes a Fuzzy-GLS estimation method that allows to improve the estimation performances of classic GLS estimator by including, in addition to traffic counts, uncertain information about starting O–D demand (i.e. outdated estimates, spot data, expert knowledge, etc.). The methods explicitly take into account the relevant level of uncertainty by taking as much advantage as possible from the few vague available data. The method is developed using fuzzy sets theory and fuzzy programming that seems to be a convenient theoretical framework to represent uncertainty in the available data. A solution algorithm for the proposed problem is also presented. The method has been tested by numerical applications and then compared to the classical GLS method under different sets of constraints to the problem.""

A fuzzy logic inference system was designed to predict the grain size of Inconel 718 alloy after upset forging. The system takes as input the original grain size, temperature, and reduction rate at forging and predicts the final grain size at room temperature. It is assumed that the ...

 Abstract-Analytical Hierarchical Process (AHP) and Fuzzy Analytical Hierarchical Process (FAHP) are two methods both used for Multi Criteria Decision Making (MCDM). Consistency Ratio (CR) is checked for all data sets fed into both these methods and weight values are compared. As well as differences between weights determined by both methods and decision values have been compared and tried to understand the nature of both methods.

Career guidance for students, particularly in rural areas is a challenging issue in India. In the present era
of digitalization, there is a need of an automated system that can analyze a student for his/her capabilities,
suggest a career and provide related information. Keeping in mind the requirement, the present paper is an
effort in this direction. In this paper, a fuzzy based conceptual framework has been suggested. It has two
parts; in the first part a students will be analyzed for his/her capabilities and in the second part the
available courses, job aspects related to their capabilities will be suggested. To analyze a student, marks
in various subject in 10+2 standards and vocational interest in different fields have been considered and
fuzzy sets have been formed. On example basis, fuzzy inference rules have been framed for analyzing the
abilities in engineering, medical and hospitality fields only. In second part, concept of composition of
relations has been used to suggest the related courses and jobs.

Industrial control systems are nowadays exposed in environments with rapid and unstable parameter changes and uses measuring equipments with critical output sensitivity. In the case of thermal gas analyzer, measurement errors are contributed by temperature, gas flow, and pressure. Error compensation is a key problem for these control systems. In recent years, it has been proven in the literature that artificial neural network (ANN) is a reliable and low cost solution to manage errors. Among all the algorithms of ANN, the back propagation is commonly used because of its simplicity and learning methodology is easy to realize. However, it has two notable drawbacks: (a) it is likely to run into local minimum, and (b) convergence is slow. Thermal conductivity gas analyzer often works in adverse surroundings, which requires fast and accurate measurements. Therefore, a strong learning network is needed. This paper proposes a novel thermal gas analyzer using adaptive neuro-fuzzy inference system. The effectiveness and validity of the proposed method is verified by simulation studies using MATLAB. Fuzzy membership rules are created to allow regulation of learning parameters. Further, the fuzzy adaptive network model is constructed to train large data samples while the high precision compensation of sensor error is realized by the improved flow. Simulation results reveal that the convergence speed and output accuracy is improved and the learning parameters in thermal gas analyzer are automatically corrected by the proposed method in comparison with the back propagation algorithm of artificial neural network.

The increasing demand of World Wide Web raises the need of predicting the user's web page request. The most widely used approach to predict the web pages is the pattern discovery process of Web usage mining. This process involves inevitability of many techniques like Markov model, association rules and clustering. Fuzzy theory with different techniques has been introduced for the better results. Our focus is on Markov models. This paper is introducing the vague Rules with Markov models for more accuracy using the vague set theory.