Use Of Fuzzy Logic Research Articles

ARCHITECTURAL AND URBAN TYPOLOGY OF CULTURAL AND HISTORICAL PLACES

The article proposes a typology of the historical places in a city for their identification and typification. Classification is based on the analysis of the structural techniques that determine the morphological features of historical places in the urban structure. The use of fuzzy logics seems to be an actual tool to achieve objectivity in the analysis of territories of different development. The hierarchy of the regulated order is determined by the following system of factors: sustainable urban framework - ordinary buildings – visual accents; building-blockbuster, visual gap. Taking into account the sustainability, the following cultural and historical places are identified: the museum cluster, cultural and historical island, cultural and historical island of a mixed type, island-type town-planning with historical buildings, modern cluster.

Analysis of Fuzzy Logic Modification for Student Assessment in e-Learning

The phenomenon of the rapid transfer of learning to online systems, such as e-Learning, has occurred massively. Institutions must ensure that student assessments run well. The characteristics of learning in e-Learning require an appropriate assessment method. The fuzzy logic method can be an option. Research shows that fuzzy logic is capable of providing flexible and objective performance evaluation. Fuzzy logic is a method that can overcome the uncertainty of transparency and objectivity of student assessments. In general, fuzzy logic applications are carried out by standards. Modification is an attempt to reveal the flexibility and to optimize the use of fuzzy logic. This study presents an analysis of fuzzy logic modification for the assessment of Algorithm and Data Structures courses held in e-Learning. These modifications include (i) modification of the parameter score with score compatibility, (ii) consequent modification of the fuzzy rules and (iii) modification of the implication process. The study results show that although the use of fuzzy logic requires more complicated procedures and tools, it can present various kinds of assessment as an option for educators to assess students in e-Learning.

The usefulness and application of fuzzy logic and fuzzy AHP in the materials finishing industry

ABSTRACT It is suggested that fuzzy logic could occupy a more prominent role in the materials finishing industry. While a number of applications have already been made to control finishing processes and help with decision making, there is clearly scope for extending the use of fuzzy logic in the industry. After surveying some of these applications, the background to fuzzy logic is described and its set theory explained. Finally, the steps involved in selecting an environmentally acceptable metal cleaning agent from possible alternatives using a fuzzy analytic hierarchy process (AHP) are described in detail. As illustration, two different sets of selection criteria ranking are considered for choosing (i) the best solvent for cleaning equipment to be used in oxygen service and (ii) for cleaning metal parts prior to further finishing treatment.

Remote diagnosis of diabetics patient through speech engine and fuzzy based machine learning algorithm

As recent development of technology, it enables patients to get treatment remotely from doctors through audio conversation. The fourth highest number of death every year is caused by diabetics. Almost 50% to 80% of patients can avoid diabetics if the cause is found at the early stage. In this paper, we propose a new methodology to detect Diabetes at an early stage and recommend few attributes in which the patient needs to be careful in order to avoid diabetics. The proposed methodology makes use of fuzzy logic and kNN classifier to find out the caution attributes and recommends them as soon as possible. The proposed algorithm detects the audio signals from patients or clinical labs to process the data. We implemented our proposed methodology on Pima Indian dataset and compared with existing algorithms and the result shows that our algorithm outperforms existing algorithms.

The use of fuzzy logic for the clean-up systems control for bunkers, containing bulk solids

The issues of eliminating the bulk solids overhanging in bunkers using pneumatic pulse devices are considered in the following article. An algorithm for automatic control of pneumatic collapse systems based on the use of fuzzy logic methods is proposed. A constructive solution for this algorithm is given, based on the assessment of the level of bulk material on the conveyor installed at the exit of the hopper. The Mamdani algorithm is used as a fuzzy inference algorithm. The fuzzy Logic Toolbox package of the MATLAB computing environment was used for modeling fuzzy systems. The use of mid-maximum and center-of-gravity methods as a defuzzification method is considered. It is demonstrated that the use of fuzzy logic makes it possible to significantly simplify the development of the control system algorithm.

Using a Fuzzy Framework for applying King’s Theory of Goal Attainment to Improve Hospital Acquired Infection Resilience

This article explores techniques for estimating Hospital Acquired Infection prevention potential through strategic nursing care delivery design and applied fuzzy frameworks. To achieve this, it evaluates the use of Fuzzy Logic directed by King’s Theory of Nursing Goal Attainment for developing a HAI resilience process model. The purpose of this model is to estimate the performance of environment of care safety based on the ability of nurses to moderate risk and respond adaptively to certain types of hospital-onset infections through strategic workflow design. The aim of this proposed approach would be to help nurses and infection control specialists in healthcare settings better understand what accessible Systems Science-based frameworks may be instrumental for analyzing and forecasting infection control systems improvement. The benefit of using Fuzzy Frameworks in nursing workflow and environment of care planning is that it allows for the leveraging of crystalized intelligence nursing staff have about their patient demography and unit-based workflow. This process allows nurse work designers to introduce and test targeted process or physical improvement strategies that make sense for their unique circumstances while providing better insight into how these interventions may work holistically with all relevant environment of care operations. This approach is made more powerful when guided by trusted optimal nursing theoretical perspectives such as King’s Theory of Goal Attainment.

Social media and sensemaking patterns in new product development: demystifying the customer sentiment

Artificial intelligence by principle is developed to assist but also support decision making processes. In our study, we explore how information retrieved from social media can assist decision-making processes for new product development (NPD). We focus on consumers’ emotions that are expressed through social media and analyse the variations of their sentiments in all the stages of NPD. We collect data from Twitter that reveal consumers’ appreciation of aspects of the design of a newly launched model of an innovative automotive company. We adopt the sensemaking approach coupled with the use of fuzzy logic for text mining. This combinatory methodological approach enables us to retrieve consensus from the data and to explore the variations of sentiments of the customers about the product and define the polarity of these emotions for each of the NPD stages. The analysis identifies sensemaking patterns in Twitter data and explains the NPD process and the associated steps where the social interactions from customers can have an iterative role. We conclude the paper by outlining an agenda for future research in the NPD process and the role of the customer opinion through sensemaking mechanisms.

Implementasi Logika Fuzzy dalam Mengoptimalkan Persediaan Barang dengan Metode Mamdani

The fuzzy logic is thought to be able to map an input space into an output space. To optimize the inventory in Affan stalls can use fuzzy logic with Mamdani method. The use of fuzzy logic is necessary to optimize the inventory in Affan stalls to avoid excess items. The study method uses literature study and data analysis with the accuracy of data reaches 83%. From this analysis can know and optimize the inventory of goods in Affan stalls with method Mamdani in January 2020 get the accuracy of the data 83% with the demand of 1,500 units, sold 2,100 units and supplies required IE 2,300.

Fluidized Bed Jet Milling Process Optimized for Mass and Particle Size with a Fuzzy Logic Approach.

The milling process is a complex phenomenon dependent on various technological and material parameters. The development of a fluidized bed jet milling model is of high practical significance, since milling is utilized in many industries, and its complexity is still not sufficiently recognized. Therefore, this research aims to optimize fluidized bed jet milling with the use of fuzzy logic (FL) based approach as one of the primary artificial intelligence (AI) methods. The developed fuzzy logic model (FLMill) of the investigated process allows it to be described as a non-iterative procedure, over a wide range of operating conditions. Working air pressure, rotational speed of the classifier rotor, and time of conducting the test are considered as inputs, while mass and mean Sauter diameter of the product are defined as outputs. Several triangular and constant linguistic terms are used in the developed FLMill model, which was validated against the experimental data. The optimum working air pressure and the test’s conducting time are 500 kPa and 3000 s, respectively. The optimum rotational speed of the classifier is equal to 50 s−1, considering the mass of the grinding product, and 250 s−1 for the mean Sauter diameter of the product. Such operating parameters allow obtaining 243.3 g of grinding product with the mean Sauter diameter of 11 µm. The research proved that the use of fuzzy logic modeling as a computer-based technique of solving mechanical engineering problems allows effective optimization of the fluidized bed jet milling process.

A New Algorithm for Daily Sea Ice Lead Identification in the Arctic and Antarctic Winter from Thermal-Infrared Satellite Imagery

The presence of sea ice leads in the sea ice cover represents a key feature in polar regions by controlling the heat exchange between the relatively warm ocean and cold atmosphere due to increased fluxes of turbulent sensible and latent heat. Sea ice leads contribute to the sea ice production and are sources for the formation of dense water which affects the ocean circulation. Atmospheric and ocean models strongly rely on observational data to describe the respective state of the sea ice since numerical models are not able to produce sea ice leads explicitly. For the Arctic, some lead datasets are available, but for the Antarctic, no such data yet exist. Our study presents a new algorithm with which leads are automatically identified in satellite thermal infrared images. A variety of lead metrics is used to distinguish between true leads and detection artefacts with the use of fuzzy logic. We evaluate the outputs and provide pixel-wise uncertainties. Our data yield daily sea ice lead maps at a resolution of 1 km2 for the winter months November– April 2002/03–2018/19 (Arctic) and April–September 2003–2019 (Antarctic), respectively. The long-term average of the lead frequency distributions show distinct features related to bathymetric structures in both hemispheres.

Simplified fuzzy logic and arduino-based controller for maximum power tracking in solar panel

Maximum power tracking for solar panel has been explored since long time ago for increasing solar panel output. Various methods have been implemented from combinational based algorithm to intelligent system, including the use of fuzzy logic. This paper demonstrates the implementation of fuzzy logic on the arduino microcontroller system. A maximum power tracking prototype is developed, and experimental assessments are conducted. Arduino uno is used for the microcontroller, small scale mechanic is developed driven by two electric motors, and 13V solar cell is used as the object. The assessments show that fuzzy logic algorithm is successfully implemented in arduino, the solar panel output is enhanced up to x% and the solar panel efficiency is up to x%.

Application of fuzzy logic in order to plan and create software for converting sound to text

The challenge of software in the field of converting sound to text is that some words have different meanings. In these situations, the functions of each one is distinguished by the use of fuzzy logic and division of the working part of the work. In this regard, the words must first be classified according to the specialized discipline. In the second place, the principles of writing should be maintained. In this regard, the points and commands and the alignment of the sentence are all items that should be considered in the software. The next item is the volume and speed of word processing and the lack of restrictions in the number of languages used. But the time problem is very important. In this regard, the use of existing codes and the optimization and remedy of the problems is a suitable method.In this research, some issues including security and maintenance of software proprietary rights, and the speed of converting sound to text and reducing noise and optimal performance of software to convert audio to text based on software method and the principles of fuzzy logic and neural network were investigated. Results showed improvement algorithm Analytical and results outcomes.

Reactive control scheme based on fuzzy behaviors for mobile robot

This paper presents the design and implementation of a behavior-based control scheme. The construction of the set of behaviors is based on the use of fuzzy logic as a means for materializing the designer’s knowledge into the behaviors. The behavior set was established by left and right wall following and obstacle avoidance. These three behaviors were programmed and coordinated by a subsumption architecture or behavioral inhibition. Behavior simulations and coordination scheme design were tested by means of real experiments using a mobile robotic platform. Finally, the results are presented, where the control actions are executed by the robotic system achieving a secure navigation.

The Use of Fuzzy Logic as Augmentation to Quantitative Analysis to Unleash Knowledge of Participants’ Uncertainty When Filling a Survey: Case of Cloud Computing

Quantitative analysis is a solid, well established mathematical technique that can be used to analyze the result of survey(s) in a specific field. Survey analysis is usually based on the study of the effect of independent variables on a dependent variable. Although quantitative analysis can use an R-Squared value as a method to measure the strength of the relationship between the independent and dependent variables, it does not capture the effect of participants' ambiguity when answering questionnaires. The source of such ambiguity stems from the process of completing the survey, whereby the respondent may have answered most of the independent questions with ease, but has difficulty in responding to the overall dependent question (or vice versa). The objective of this paper is to demonstrate the use of fuzzy logic as a mechanism to measure the uncertainty faced by participants when filling a questionnaire. Based on the participants' responses to the independent variables, the proposed technique uses fuzzy logic inference to measure the subjectivity (qualitative aspect) of the participants' response to the dependent variable. Beyond quantitative analysis, augmentation with such a fuzzy module can provide clearer picture to analysts when analyzing the survey results.

Fuzzy Logic in Dynamic Parameter Adaptation of Harmony Search Optimization for Benchmark Functions and Fuzzy Controllers

Nowadays the use of fuzzy logic has been increasing in popularity, and this is mainly due to the inference mechanism that allows simulating human reasoning in knowledge-based systems. The main contribution of this work is using the concepts of fuzzy logic in a method for dynamically adapting the main parameters of the harmony search algorithm during execution. Dynamical adaptation of parameters in metaheuristics has been shown to improve performance and accuracy in a wide range of applications. For this reason, we propose and approach for fuzzy adaptation of parameters in harmony search. Two case studies are considered for testing the proposed approach, the optimization of mathematical functions, which are unimodal, multimodal, hybrid, and composite functions and a control problem without noise and when noise is considered. A statistical comparison between the harmony search algorithm and the fuzzy harmony search algorithm is presented to verify the advantages of the proposed approach.

Diffuse system simulating wheat productivity by nitrogen and temperature in the use of biopolymers

ABSTRACT Fuzzy logic can simulate wheat yield by nitrogen and temperature nonlinearity, validating the use of hydrogel biopolymer. The objective of this study is to adapt the fuzzy logic model to the simulation of nitrogen biomass and wheat grain yield and non-linearity of the maximum air temperature, under the conditions of use of the hydrogel biopolymer, in high and low N-residual release systems. The study was conducted in 2014 and 2015, in Augusto Pestana, RS, Brazil (28 ° 26 ‘30’ latitude S and 54 ° 0 ‘58’ longitude W). The experimental design was a randomized block design with four replications in 5 x 5 factorial, for hydrogel doses (0, 30, 60, 90 and 120 kg ha-1), added in the furrow next to the seed, and N-fertilizer doses. (0, 30, 60, 90 and 120 kg ha-1), applied at the phenological stage V3 (third expanded leaf) as top-dressing, respectively. The pertinence functions together with the quantitative and linguistic values for the input and output variables are suitable for the use of fuzzy logic in the wheat yield simulation. The fuzzy model made it possible to estimate the values of biomass and wheat grain yield by nitrogen and non-linearity of the maximum air temperature under the conditions of use of the hydrogel biopolymer in high and low N-residual release systems.

Internet of things networks predictive risk assessment method and security management

The methodology of predictive security violation risk assessment based on the use of fuzzy logic is offered. Demonstrates one risk assessment methodology use for IoT-network in presence of data about protocols used in network wireless devices. Alternative methodology for risks predicting when at the initial stage experts estimate input parameters, with subsequent data processing using the hierarchical methodology based on fuzzy inference systems that can reduce the influence of subjective expert evaluations of the researched object is offered. Numerical estimates of risk, despite qualitative character of expert estimates of input parameters are received.

Local Mutual Exclusion algorithm using fuzzy logic for Flying Ad hoc Networks

The Local Mutual Exclusion (LME) problem is a variant of classical Mutual Exclusion (ME) problem and can be considered as an extension of dining philosopher problem. In LME, no two neighboring nodes can enter the critical section (CS) simultaneously, whereas two non-neighboring nodes can be in their CS simultaneously. The resource allocation problem in Flying Ad hoc Networks (FANETs), is relatively an unexplored area despite having several potential applications. The present paper proposes LME problem for FANETs and provides a leader-based algorithm named as Request Collector Local Mutual Exclusion (RCLME) for the same. To the best of our information, LME problem is introduced first time in Flying Ad hoc Networks. The striking feature of the proposed algorithm is the introduction of a fuzzy logic-based leader election that considers the node speed, node direction, link quality, and the distance from the resource. The correctness proof of the RCLME algorithm has been presented. The simulation results show that RCLME algorithm significantly outperforms other related algorithms available in the literature; specially, when the number of nodes is large. The use of fuzzy logic and request collector improves the efficiency, fault tolerating capacity and ability to handle volatility.

Application of Fuzzy Logic Techniques for Biogeochemical Characterization of Dams Affected by Acid Mine Drainage (AMD) Processes in the Iberian Pyrite Belt (IPB), Spain

Water is one of the receptors media more affected by the environmental impacts, especially caused by mining sulfides exploitation. Acid mine drainage (AMD) is the main problem associated with these mining operations, producing extremely high impacts, and in many cases irreversible, still remaining nowadays. Diatoms, are the taxonomic algal group most used in environmental studies, to assess the water quality of rivers. From a monitoring perspective, the diagnosis of AMD contamination through the use of diatoms has proved to be an effective ecological tool to assess the impact and select the preventive and corrective measures more adequate to treat these impacted sites. In the present work, the existing relationships between biological and physicochemical indicators of acid mine drainage processes (AMD) in all the reservoirs affected by AMD in the Iberian Pyrite Belt (IPB) were studied through the use of fuzzy logic and data mining techniques that in contrast to the classic statistical treatments. The fuzzy rules show the relationship between biological and physical-chemical indicators, demonstrating the presence of a perfect correlation in all cases; thus, the numbers of species and pH have the same behavior, and inverse to that presented by the percentage of Pinnularia and the metallic charge and sulfates. These techniques improve the work considerably and make easier the knowledge of the involved processes, allowing a better discrimination of the diatoms responses to the stimuli caused by the hydrochemical changes imposed by the processes affecting water quality.

Fuzzy logic for fine-scale soil mapping: A case study in Thailand

Conventional soil survey methods are labor intensive and prohibitively expensive considering the area to be covered. Unfortunately, the current soil survey products are not adequate, either categorically or cartographically, and cannot be easily downscaled for its application at farm-level. On the other hand soil is a continuous variable and does not have abrupt boundaries in nature. One soil type can change gradually to become another class. This creates problem in delineating soil boundaries due to overlapping of classes. In this situation fuzzy logic can be useful. In conventional soil survey, this is solved by creating mapping units such as consociation, association or complex. In consociation the delineated areas are dominated by one soil type (at least 75%) with some inclusion of other soils. When dissimilar soils occur in a consistent repeating pattern, it is mapped as an association. In classification using fuzzy logic a pixel may have multiple class membership and the one with the highest membership or similarity value gets the class label. The main objective of the study is to assess the usefulness of fuzzy logic in increasing efficiency in soil mapping. The study was conducted in Lomsak, Phetchabun province in Thailand. An expert system was used whereby rule-based reasoning was applied for mapping soil series and topsoil texture in which the soil-landscape relationship was taken into account. Lithology and terrain parameters were used as predictor variables. This resulted in mapping 17 soil series and 10 topsoil texture classes in a complex landscape. In the conventional soil survey technique, it is possible to map only 8 soil series at 1:50,000 scale, indicating that detail soil mapping is possible by using fuzzy logic. The accuracy of the fuzzy logic derived soil series map was tested using a set of evaluation data. The result showed an average accuracy of 70%. Fuzzy logic has the potential for reducing inconsistency and costs associated with the traditional soil mapping processes as mapping can be carried out with a relatively low density of soil samples. The research results can be used to support soil survey works in complex landscapes at sub-watershed scale.