Fuzzy Logic Tool Research Articles

Identification of Potential Earthquake Source Zones in Areas of Recent Tectogenesis Based on Geological and Geomorphological Factors and Tools of Fuzzy Logic: The Greater Caucasus

Identification of Potential Earthquake Source Zones in Areas of Recent Tectogenesis Based on Geological and Geomorphological Factors and Tools of Fuzzy Logic: The Greater Caucasus

Enhancing Control Systems through Type-3 Fuzzy Logic Optimization

The advancement of new tools in the field of control systems is a contemporary development. This work introduces the utilization of Type-3 fuzzy logic, a relatively recent concept that has been applied across various disciplines. In our case, a Type-3 fuzzy system is designed to enhance the optimization of parameters within the harmony search algorithm, specifically tailored for a control problem. Through a series of experiments, the efficacy of this novel Type-3 fuzzy logic tool is put to the test. Previous studies have primarily explored Type-1 and Type-2 fuzzy logic. To assess the performance of this new Type-3 fuzzy logic tool, a comparative analysis of results is conducted using statistical testing. The introduction of Type-3 fuzzy logic in the control domain represents a novel and innovative approach. This approach extends beyond the conventional Type-1 and Type-2 fuzzy logic, showcasing the dynamic evolution in the field. Results obtained through experimentation are analyzed, and statistical tests are employed to determine whether the Type-3 fuzzy logic tool yields superior outcomes compared to its predecessors. By doing so, this study contributes to the growing body of research that explores the potential benefits of Type-3 fuzzy logic and its application in control systems, offering new perspectives and opportunities for further advancements in the field. We have to mention that the utilization of Type-3 fuzzy logic in enhancing metaheuristics is a relatively new trend, and in this work, this research has extended this to the realm of harmony search. In addition, the application of the optimal design of the ball-and-beam fuzzy controllers has not been previously carried out with the Type-3 fuzzy harmony search algorithm, which is the novelty of this study.

Wind farm site selection using GIS-based mathematical modeling and fuzzy logic tools: a case study of Burundi

Introduction: The electricity generated from nuclear plants and petroleum-based products has a negative influence on the environment as a whole. It has shown the utility to search out and promote the utilization of renewable, environmentally friendly, and sustainable energy sources such as solar, wind, and geothermal. Nowadays, Wind energy resource has quickly emerged as the world’s fastest-growing energy source.Methods: However, the selection of the most suitable places for developing a wind farm is a crucial challenge that can be seen as a problem of site selection, which involves numerous conflicting variables. Therefore, it is classified as an MCDM (multi-criteria decision-making) problem. The main objective of this research is to determine the best locations in Burundi for the installation of wind farms. The Fuzzy Analytic Hierarchy Process (FAHP) was used to weigh the criteria considering their relative importance. This study considers several key factors when determining the optimal location for a wind farm. These factors include wind speed, slope, proximity to the grid network, distance to roads, and land use/land cover (LULC). Furthermore, a geographic information system (GIS) is utilized to generate the final suitability wind farm locations map.Results and Discussion: The obtained results indicate that 20.91% of the whole study area is suitable nevertheless, only 1.96% is tremendously suitable for wind turbine placement. The western part of Burundi is the optimal area for constructing a wind farm, and the most is in Lake Tanganyika.

Assessing the Degree of Sustainability in Extractive Reserves in the Amazon Biome Using the Fuzzy Logic Tool for Decision Making

The Extractive Reserve (RESEX) was designed to protect rubber tapping communities and their livelihoods, thus guaranteeing environmental health. This study was carried out between 2021 and 2023 and aimed to propose a methodology based on the fuzzy logic method to assess the degree of sustainability in RESEXs in the state of Amazonas, Brazil. For this assessment, 10 indicators were used, represented through input variables in the fuzzy inference systems represented by the Environmental Subsystem (ES), Economic Subsystem (ECS), Social Subsystem (SS), and Institutional Subsystem (IS), with performances that converged so that the Sustainability System in the RESEX (SRE) system reached a performance value of 30.0, on a scale of 0 to 100, which translates into low sustainability in these spaces in the state of Amazonas. The methodology’s ability to represent the main phenomena that impact sustainability in the RESEX studied through linguistic variables and weight them in their complexities, as well as inferring a set of decision rules that reflect the knowledge of experts and which aim to quantitatively contextualise sustainability under uncertainty and imprecision in these areas, makes it a viable instrument to be applied and used by managers and decision-makers in the management of these spaces.

Strategic Priorities for the Development of Food Security of the State Taking into Account Hybrid Threats and Challenges

Relevance. Food security is one of the most urgent and complex problems of the modern world. In the context of globalization, climate change, economic fluctuations and other factors, ensuring the stability and reliability of food security is becoming a complex task that requires effective strategies.The purpose is to analyze and evaluate strategic priorities in the field of food security, taking into account complex hybrid threats and challenges. Objectives: identification of strategic alternatives; development of a mathematical model with fuzzy variables and rules for evaluating strategic alternatives; analysis of evaluation results to identify the most effective strategic directions.Methodology. The research methodology included the use of fuzzy logic methods to build a mathematical model for evaluating strategic alternatives.Results. As a result of the study, it was revealed that the strategic alternative S1 received the highest rating, emphasizing its key importance for the sustainability of the food system. Alternatives S7, S9, S4 and S3 also have high ratings, which makes them potentially effective for ensuring food security. Alternatives S10, S8, S2, S6 and S5 are less of a priority, but are important for reducing various risks associated with food security, such as lack of food and vulnerability of supplies.Conclusions. The results of the study allowed us to conclude that the use of the fuzzy logic tool provides an opportunity to conduct a deeper and more comprehensive analysis of complex factors affecting food security. This approach allows us to take into account the uncertainty and multidimensionality of data related to the food system and introduce more accurate modeling of this dynamic area. Such a method enriches the decision-making process in the field of food security, contributing to the development of more effective strategic decisions and management approaches that take into account a variety of factors and their interaction. This contributes to improving the quality of research and helps to form more rational and informed strategies that contribute to ensuring the stability and reliability of food security.

МЕТОДИКА ОЦЕНКИ КОМФОРТНОСТИ ПЕРЕВОЗКИ ПАССАЖИРОВ ЖЕЛЕЗНОДОРОЖНЫМ ТРАНСПОРТОМ ДЛЯ МИНИМИЗАЦИИ РИСКОВ СВЯЗАННЫХ С ЧЕЛОВЕЧЕСКИМ ФАКТОРОМ В ПРОЦЕССЕ ВЕДЕНИЯ ПОЕЗДА

The paper solves the problems of assessing the smooth running of a passenger train, the quality and comfort of passenger transportation by rail, as well as determining the level of professional competencies of locomotive crew members. A comprehensive computer model of a passenger train is developed, which makes it possible to study all the processes of controlling traction equipment and train brakes that affect energy efficiency, safety and dynamics of rolling stock. Using fuzzy logic tools, a technique is developed for rating employees of locomotive crews according to the criterion of ensuring smooth running of the train. The results of experimental trips by passenger trains on sections of the North Caucasus Railway are presented. The dependences of the locomotive traction force, the speed and the longitudinal jerk of the passenger train cars are obtained.

Present and future situation of West Nile virus in the Afro‐Palaearctic pathogeographic system

West Nile virus (WNV) is a globally widespread arthropod‐borne virus that poses a significant public health concern. Mosquitoes transmit the virus in an enzootic cycle among birds, which act as reservoirs. Climate plays a crucial role in these outbreaks as mosquitoes are highly influenced by climatic conditions, and bird migrations are also affected by weather patterns. Consequently, changes in climate can potentially impact the occurrence of WNV outbreaks. We used biogeographic modelling based on machine learning algorithms and fuzzy logic to analyse and evaluate separately the risk of WNV outbreaks in two different biogeographic regions, the Afrotropical and the Western Palaearctic region. By employing fuzzy logic tools, we constructed a comprehensive risk model that integrates the Afro‐Palaearctic system as a unified operational unit for WNV spread. This innovative approach recognizes the Afro‐Palaearctic region as a pathogeographic system, characterized by biannual connections facilitated by billions of migratory bird reservoirs carrying the disease. Subsequently, we forecasted the effects of different climate change scenarios on the spread of WNV in the Afro‐Palaearctic system for the years 2040 and 2070. Our findings revealed an increasing epidemic and epizootic risk south of the Sahara. However, the area where an upsurge in risk was forecasted the most lies within Europe, with the anticipation of risk expansion into regions presently situated beyond the virus' distribution range, including central and northern Europe. Gaining insight into the risk within the Afro‐Palaearctic system is crucial for establishing coordinated and international One Health surveillance efforts. This becomes particularly relevant in the face of ongoing climate change, which disrupts the ecological equilibrium among vectors, reservoirs, and human populations. We show that the application of biogeographical tools to assess risk of infectious disease, i.e. pathogeography, is a promising approach for understanding distribution patterns of zoonotic diseases and for anticipating their future spread.

Hydrochemical characterisation of a landslide prone area, South Western Ghats, India

ABSTRACT This study focuses on the Manimala River Basin (MMRB) situated in the Western Ghats region of Kerala, which has been significantly affected by landslides. The water quality in the MMRB is likely to be impacted by heavy rainfall and the resulting debris flows. A comprehensive analysis was conducted for 157 water samples collected from the MMRB, with an objective to evaluate the hydrogeological conditions and estimation of 23 physico-chemical parameters to determine the water quality. Pearson’s correlation matrix for geochemical data was performed to investigate the relationships among physical and chemical parameters, and various ions in the MMRB. The present study also aimed to identify the dominant geochemical facies present in the water samples and determine the geochemical processes responsible for modifying the hydrochemistry. The results revealed that elevated concentrations of Ca2+ and SO4 2- ions, which exert influence on the hydrochemistry of the region. Moreover, we utilized a fuzzy logic tool to categorize the water samples based on a water quality index, which indicated that approximately 92% of the MMRB samples are suitable for human consumption. This study offers valuable insights into the interplay of geochemical factors and water quality assessment, contributing to effective strategies for water resource management and conservation.

Building MLR, ANN and FL models to predict the strength of problematic clayey soil stabilized with a combination of nano lime and nano pozzolan of natural sources for pavement construction

The current study aims at predicting the strength of the problematic clayey soils treated with combinations of pozzolan of natural sources and lime powder when added as soil additives at a nano scale. Multiple linear regression (MLR), artificial neural networks (ANN) and fuzzy logic (FL) tools were employed in the analytical study. The variables of the present study include the following: nano pozzoaln of natural source (NNP) content, nano lime content (NL), median particle size of NNP, active silica content of NNP (SiO2active), Initial liquid limit (ILL) and initial plastic limit (IPL) of the investigated soils. NNP was added at five percentages, i.e. 0%, 0.5%, 1%, 1.5% and 2%, while NL was added at five percentages, i.e. 0%, 0.3%, 0.6%, 0.9% and 1.2%. Three median particle sizes namely 50, 100 and 500 nm size were studied. Based on the different investigated soils and combinations, 120 soil mixtures were prepared and tested. California bearing ratio (CBR) and plasticity index (PI) were particularly examined. CBR tests were conducted at a soaked condition on specimens compacted to a maximum dry density (MDD) at the optimum moisture content (OMC). PI values were obtained following the Atterberg limits test. Based on the results of the performance criteria of the developed predictive models, it can be concluded that the CBR and PI of the expansive clayey soils can be effectively predicted using ANN and FL techniques. The results obtained by MLR were far from those obtained by both ANN & FL. In addition, ANN tool was slightly more accurate than FL as far as prediction of CBR and PI is concerned. The higher capability of ANN & FL models in predicting CBR & PI values, which generally obtained through time-consuming and expensive tests, could be useful for geotechnical engineers to assess or design a new pavement project. Further, it is recommended to do a re-evaluation of the current study in future, particularly when more data is available in the literature.

Artificial Intelligence Detection System of Radioactive Nanocomposites in Liquid-Filled Containers for Nuclear Security

Nuclear terrorism resulting from the illicit trafficking of nuclear and radioactive materials consists of a serious threat against the security of countries. Hence, the transportation of hidden nuclear materials in large-scale cargos has emerged as an important public issue that requires immediate attention. The security architecture should merge the nuclear security systems and execute a procedure for the detection of nuclear and radioactive materials. In this regard, the detection of special nuclear materials (SNMs) in liquid-filled cargo containers is an essential matter of homeland security because of the difficulties imposed by liquids in performing efficient manual inspection. This paper presents a new artificial intelligence (AI) system implemented with fuzzy logic tools for detecting composite materials, including Pb-Th, Pb-U, and Pb-Co, in containers filled with water by utilizing optical signature information obtained with COMSOL. The developed AI system and its underlying method are validated for a scenario of detecting Pb-Th, Pb-U, and Pb-Co in water-filled containers.

A Fault Detection and Protection Scheme for a 200 MVA Transformer using Fuzzy Logic

The paper elucidates a fault detection and protection scheme for a 200MVA transformer using Fuzzy logic. Fuzzy logic (FL) tool box in MATLAB/ SIMULINK software was utilized in the simulation system that diagnosed transformer faults and also monitors its operating conditions. Current and rate of change of current with time have been identified as the input variables, duly represented in the programme as “Error” and “Error-Dot”. These variables have their universe of discourse from -1.5 to 1.5 and from -10 to 10 respectively. Fuzzy logic sensor is designed to monitor the current (i) conditions of the transformer at both ambient and full load. The results from the research show that whenever the output response is zero the current in transformer is normal. This is obtained when input values of [0] and [0] are injected into the system to produce a response of “6e-017” which is approximately zero. Whereas if the output response is greater than zero it implies that the transformer current is rising beyond normal and protection scheme should be alerted. This condition is achieved when input values of [-1.5] and [5] are used on the system to give a response of “+5”. However, if the response is less than zero then the transformer current is below normal, hence the protection scheme should be alerted. To investigate this, input values of [1.5] and [-5] gives a response of “-5”.

Tracking of Manoeuvring Target Using Fuzzy Logic Augmented H-Infinity Filter

Conventionally for target tracking, Kalman filter and closely related algorithms are used. These filters inherently are as such not robust. In this paper, fuzzy logic augmented H-infinity filters are proposed for target tracking application. Initially, fuzzy logic is used at filter level to eliminate or reduce local estimation errors and then, an additional fuzzy system is used to minimize effects of outliers and estimation errors during data fusion process. An adaptive H-Infinity filter using fuzzy degree of matching is also proposed for target tracking. The performance of these algorithms is evaluated using MATLAB and its fuzzy logic tool box. Very encouraging results have been obtained with the newly proposed algorithms for target tracking.

Application of Fuzzy Logic and SNA Tools to Assessment of Communication Quality between Construction Project Participants

The purpose of this research is to study the communication network among the participants in a construction project. The proposed approach contains the solving of the following tasks: identification of the key factors that affect the communication quality; calculation of the “communication quality” indicator between each pair of participants using fuzzy logic; and evaluation of the key measures of centrality using the tools of a Social Network Analysis. Solving the set tasks can help break the problem of the low level of efficiency of construction project deliveries. This study was conducted when the design stage was already complete and the construction project had 17 participants. We used the following factors influencing communication quality: timeliness, understanding, bidirectionality, use of IT tools in communication acts and adequacy. The use of fuzzy logic tools can minimise the subjectivity of the qualitative data obtained from the questionnaires. The analysis of five centrality measures showed that “Project manager”, “Chief engineer”, “Construction site manager”, “Construction works manager” and “Architect” had the greatest values in comparison with other network participants. On the one hand, this organisational structure of communication can be considered correct because the main information flows through the project managers, who make the decisions. On the other hand, this indicates a significant dependence of the construction project on these participants and, in the event of certain risk events, may lead to a decrease in the efficiency of its implementation. The methods presented in this article can be used in project management to analyse a real communication network.

A Fuzzy Logic Approach to Predict Tensile Strength in TIG Mild Steel Welds

Welding defects influence the desired properties of welded joints giving fabrication experts a common problem of not being able to produce weld structures with optimal strength and quality. In this study, the fuzzy logic system was employed to predict welding tensile strength. 30 sets of welding experiments were conducted and tensile strength data was collected which were converted from crisp variables into fuzzy sets. The result showed that the fuzzy logic tool is a highly effective tool for predicting tensile strength present in TIG mild steel weld having a coefficient of determination value of 99%.

A fuzzy logic assessment framework for collaborative development of product-service systems

The development and value chain management of product-service systems (PSS) requires companies to look for new capabilities, regarding the disparate components of a PSS. However, interfirm collaboration in this context presents several particularities which may be challenging for the stakeholders and can lead to project failure. In this regard, there is still limited literature addressing frameworks and tools to manage the collaborative aspects of PSS from an organisational point of view. This paper presents a methodology to develop a framework to support companies in choosing suitable partners in a PSS development project and to improve collaboration. Thus, an assessment model is built using key performance indicators (KPIs) based on important collaboration performance factors, with the help of a fuzzy logic tool. This model is then tested and validated in two different PSS case studies.

Financial Performance Assessment by a Type‐2 Fuzzy Logic Approach

Any company must constantly innovate if they want to maintain its market share in the present cutthroat and unstable industry. Innovation has a big influence on consumer behavior, yet it goes against the principles of sustainability. The issue of sustainability has become crucial to their company’s growth. In order to evaluate a business firm’s sustainability performance statistically, a new and effective fuzzy logic tool is created. Evolution and assessment are performed by a novel interval type‐2 fuzzy logic inference system. The judgment of the inference system is carried out on the basis of type‐2 fuzzy logic (T2FL), principal component analysis (PCA), and statistical data analysis. The main input variables include corporate environmental performance (CEP) and corporate financial performance (CFP). The suggested approach can effectively examine a corporation’s sustainable performance, according to experimental findings. A unique approach that makes use of language variables and if‐then logic to assist quantitative business sustainability events is the link between CEP and CFP. The recommended test will provide senior administrative leaders with useful information to supervise natural concerns correctly and gauge their commitment to company success.

Особенности предоставления финансовой поддержки субъектам малого бизнеса рыбной отрасли с использованием продукционной модели базы знаний

The article highlights the procedure of selecting applications for state financial support for small businesses in the fishing industry. Criteria for expert evaluation of applications have been defined taking into account industry specifics and including the following blocks: “Compliance with formal requirements”, “Type of activity”, “Justification of the requested funding”, “Socio-economic contribution to the region”. The principles of developing the evaluation criteria are generalized. The examination procedure algorithm taking into account the observance of formal requirements at the first stage of the expertise has been worked out. The algorithm provides for the functionality of clarifying the type of activity and conducting assessment according to the relevant criteria. Aggregated indicators of expert assessments reduced to a linguistic description “high”, “medium”, “low” are obtained. The system of trapezoidal membership functions on the 01-carrier (five-factor 01-classifier) is illustrated. The applicability of fuzzy logic tools for the tasks of multi-criteria assessment and management decision-making is substantiated. A base of rules for fuzzy production has been developed, consisting of 9 rules and a set of management decisions on financial support. The implementation of the decision-making procedure as a fuzzy production model built on using FuzzyLogicToolbox is shown. The conclusion about the possibility of using the results in the design of intelligent decision support systems in the field of financing small and medium-sized businesses in the fishing industry is made. It has been stated that the fuzzy production system and the expert evaluation algorithm can be projected onto other branches of the national economy as a result of the configuration of the constituent elements.

A fuzzy logic model for evaluating the motivation for high-quality publications

This paper proposes a fuzzy logic model for evaluating stakeholder motivation for high-quality publications. Conceptually, the model is based on stakeholder theory and Vroom's expectancy theory of motivation. Instrumentally, tools of fuzzy sets, fuzzy logic, and expert evaluations are at its core. The model is suitable for any university. Further, it reflects university specificity, using specific motivational factors in one of the evaluation procedures. The model easily evaluates the level of motivation by processing vague, subjective perceptions. It was applied at a Bulgarian university through a comprehensive survey that included 106 participants and performed well. The model contributes to the advancement of management science by theoretically enriching research management and organizational behaviour and complementing their tools. Expected practical implications are improved university management and better research results based on well-grounded decisions about research, people, and performance.

Fuzzy Logic Tools Application to the Characterization of Stress-Strain Processes in Waste Construction Dam Geopolymers: A New Circular Mining.

The ceramics industry dedicated to the manufacture of building materials is a very significant cause of environmental pollution, and various research projects are being carried out to reduce the associated environmental impact. One of the most important research lines is the generation and development of new materials, from waste, through more sustainable production processes. All of this is framed in circular mining. In this research study, geopolymers were developed with biomass bottom ashes and brick dust in order to replace the traditional ceramics used to construct bricks. For this, different families of test tubes were formed with different percentages of both residues, and their physical and mechanical properties were studied. In this way, the properties of geopolymers could be compared with traditional ceramics. In addition, in order to determine the cause-effect relationships between physical properties and compressive strength, data were processed using fuzzy logic and data mining techniques. The results showed the feasibility of geopolymers generation with biomass bottom ashes and brick dust with acceptable properties to replace conventional ceramics. In addition, the fuzzy logic analysis allowed for establishing clear and objective relationships between the physical properties and the compressive strength of the geopolymers, with the aim of developing the highest quality geopolymer.

Modeling of Basic Processes of Labor Market Functioning and Development: Methodological and Practical Aspects

The development of the digital economy causes cardinal socio-economic shifts, including those in the field of labor relations. Therefore, the study of basic processes of functioning and development of the labor market is an urgent task. Research methods: generalization, comparison, analysis and synthesis, induction and deduction, structural-logical analysis, monographic method, statistical modeling methods, machine learning methods, neural network modeling, fuzzy logic. The purpose of the article is to develop a methodological approach to the study of basic processes of functioning and development of the labor market under the conditions of digitalization. The hypothesis of the study – the digitalization of the economy activates structural shifts in the labor market, which can cause imbalances that can be eliminated through the development of human potential. In the course of the study, it was found that the existing methods and tools in this area are not sufficient for diagnosing the labor market under the conditions of digitalization. The article proposes the author’s methodology of analysis, based on two complex parameters: flexibility and social protection. Also, using the tools of fuzzy logic, an approach to assessing the level of social security and protection of the population was developed. The use of the approaches proposed in the article will make it possible to determine the specifics of the development of labor resources and the ongoing transformations in the structure of employment under the influence of modern technology and will also make it possible to substantiate measures of state regulation and support adequate to the challenges of our time.