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With the enormous growth in the public and private vehicles fleet, traffic congestion is increasing at a very high rate. To deal with this, an intelligent mechanism is required.Therefore, this work proposes a novel Neuro-fuzzy based intelligent traffic light control system, which accounts for vehicle heterogeneity by dynamically generating traffic light phase duration considering the real-time heterogeneous traffic load. For this purpose, the proposed model establishes peer-to-peer connections among neighboring traffic light junctions to fetch the respective real-time traffic conditions and congestion. A fuzzy membership function is utilized to generate an intelligent traffic light phase duration. Further, to obtain an effective fuzzy membership function input value considering real-time heterogeneous traffic scenarios, an adaptive neural network is utilized. The proposed system adopts three execution modes: Congestion Mode (CM), Priority Mode (PM), and Fair Mode (FM). It automatically activates and switches to the best mode based on the live traffic conditions. The performance of the proposed model is evaluated via a realistic simulation on the Gwalior city map of India using an open-source simulator known as Simulation of Urban Mobility (SUMO). The results evident the effectiveness of the proposed model over the existing state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Environment protection and basic health improvement of all social communities is now considered as one of the key parameters for the development. It has become a responsibility for both industry and academia to optimize the usage of finite natural resources and preserve them. Efficient promotion and strategic marketing of Eco Friendly products can contribute to this development. It is important to consider any market as a heterogeneous mix, which requires well-organized and intelligent split or segmentation. A survey was conducted in Kolkata, metropolitan city in India, through a structured questionnaire to measure Perceived Environmental Knowledge, Perceived Environmental Attitude and Green Purchase Behavior associated to 18 product categories identified by Central Pollution Control Board for Eco Mark Scheme, 2002. Two hundred and twenty three data inputs from the respondents were analysed for this study. Here in this study a fuzzy rule based clustering technique was performed to segregate customers into two sections considering three parameters like Perceived Environmental Knowledge, Perceived Environmental Attitude and Green Purchase Behavior associated to Eco friendly product, which acts as an input variable. The rule base has linguistic variables like Significantly High, Little High, Medium, Little Low and Significantly Low and output as "Eco friendly" or "Non-ecofriendly" consumers. A set of 5 × 5 × 5 = 125 rules were developed for output determination. They were designed manually and the method is applied for detection of a set of good rules. Thirteen such good rules were identified through Fuzzy Reasoning Tool, which can lead to better Decision Making and facilitate the marketers to develop strategy and take up effective marketing decisions. [ABSTRACT FROM AUTHOR]

• A Fuzzy Inference system is developed for site suitability evaluation of water harvesting structures. • FIS showed high suitability for check dams and farm ponds in the study area. • Suitability maps are envisaged to aid the participatory watershed management in reaching efficient decisions. Watershed management (WM) aims at enhancing the water availability in rainfed areas through water conservation structures, which facilitate storage of water and recharge to ground water. Identification of suitable locations for placing these structures play a major role in the effectiveness of the water conservation. Site suitability evaluation of water conservation structures is performed through an assessment of various biophysical and socio-economic factors. Many of these factors are expressed in linguistic terms rather than precise numeric values, and therefore the output of the evaluation gets subjective. In this study, a fuzzy inference system (FIS) is developed for site selection of water harvesting structures (check dams, farm ponds, and percolation tanks), owing to its capability to handle linguistic data effectively. The suitability zones were identified using the slope, soil permeability and runoff potential as input variables to the FIS. Trapezoidal membership function (MF) was considered for the input and output variables for the fuzzy model and MF parameters were obtained from literature and expert knowledge. The developed FIS is illustrated through an application to Kondepi watershed, Andhra Pradesh, India. The FIS categorized the majority of the watershed area into high suitability class for both farm ponds and check dams. However, the watershed characteristics were not conducive for percolation tanks according to the FIS. A sensitivity analysis of the FIS parameters suggested that the check dam suitability was sensitive to the soil permeability classes. The suitability maps from the FIS were in good agreement with the location of the existing structures in the watershed, suggesting potential use of the developed FIS in WM decisions. [ABSTRACT FROM AUTHOR]

A method for identification of most probable paleochannels in and around "Chandraketugarh" (an archeological site in the western part of Ganges Delta) was developed through remote sensing techniques using fuzzy inference system (FIS). The method was adopted considering the uniqueness of the geomorphology in terms of terrain homogeneity of the area. In order to categorize different geomorphological features, NDVI, NDWI, and elevation datasets were generated using multispectral images (LISS III) and CARTOSAT I datasets. Based on the unique spectral signatures of the different geomorphological units, the said datasets were critically examined to be utilized as the input parameters of the employed FIS-based image segmentation method. The result of subsequent analysis lead to development of a land use/land cover (LULC) map which portrayed inferred paleochannels. The developed method was validated with reference to a finer resolution image and ground truth datasets. It is concluded that the newly developed FIS-based method is quite efficient for identifying probable paleochannels in a terrain where slope variation is minimal and geomorphology does not seem to have been strongly affected by structural elements. [ABSTRACT FROM AUTHOR]

Fluoride contamination in drinking water is a serious public health concern across the world, and more than 90 million people in India are affected by health risks associated with fluoride. Though the fatality due to fluoride chronic toxicity is uncommon, the exposure to fluoride at different concentration levels shows various adverse health effects such as dental and skeletal fluorosis, multiorgan failure, cognitive and behavioural effects. Hence, the objectives of the present study are to understand the hydrogeochemistry and drinking water suitability of groundwater of the Sira region, Karnataka, India, and to understand the occurrence of fluoride and its health risks using the United State Environmental Protection Agency (US EPA) method and fuzzy logic concepts. Forty-six samples were collected from each pre and post-monsoon season. The hydrogeochemistry studied through Chadha's diagram and Gibb's diagram indicated that the groundwater in this region is of Na-Cl type and the hydrogeochemistry is majorly controlled by rock-water interaction and followed by evaporative dominance. Water quality parameters were compared with drinking water standards guidelines, and the results showed that around 50% of the samples were contaminated with fluoride. The occurrence of high levels of fluoride in the study region is associated to the presence of granitic rocks and it is influenced by high pH and low calcium dissolution in the groundwater. Based on US EPA method, the order of population group under the risk of dental and skeletal fluorosis, is children > adolescents > adults. A fuzzy inference system model is developed to assess the health risk due to fluoride and its output gives severity levels of each type of health risk, i.e. dental caries, dental fluorosis and skeletal fluorosis. The results of the application of the fuzzy inference system model in the Sira region showed that the children (< 8 Yr.) are more susceptible to the moderate risk of dental caries, dental fluorosis and skeletal fluorosis. Whereas adolescents (8-18 Yr.) and adults (> 18 Yr.) are less susceptible to low-very low risk. Hence, health risks associated with fluoride can be better addressed with the help of a fuzzy inference system model which can be used for more reliable and grounded results to improve the quality of decision-making., (© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)

Polypropylene is a versatile thermoplastic resin available in a wide range of formulations for engineering applications. This paper presents a new approach to predict the quality of polypropylene in petrochemical plants. A model is constructed based on a large number of data collected from a renowned petrochemical plant in India and used to predict the polypropylene quality through the proposed approach. The quality of polypropylene depends on the indices like melt flow index and the xylene solubility of the product. The parameters controlling these two indices are hydrogen flow, donor flow, pressure and temperature of polymerization reactors. Using these four input and two output parameters, four Mamdani fuzzy inference systems are formed depending on the different membership functions of the variables. The model outcomes are then compared with the collected plant data and a sequence of statistical data analyses selects the most suitable model among them. Some sensitivity analyses with respect to some parameters are also performed to validate the proposed models. The raw materials for producing polypropylene are very much costly specially the catalyst teal. So if the desired grade of PP is not achieved by the trial and error run then the production cost becomes uncontrollable. With the help of our proposed approach by controlling some parameters during the production phase, the quality of polypropylene can be improved. Thus it will save both time and cost by reducing the yield of non-prime, off-grade products obtained by the conventional procedure. [ABSTRACT FROM AUTHOR]

A major shift has been observed in the banking sector in recent times worldwide. The Indian banking sector has witnessed a massive transformation over the last few years due to the introduction of certain government policies. Banks are now considering the development of new service quality policies and strategies that promote customer satisfaction and loyalty. The present study attempts to evaluate the service quality of Indian banks from the customer's perspective. We propose a fuzzy inference system for predicting various dimensions of service and identifying deficient service dimensions that promote effective strategy design. [ABSTRACT FROM AUTHOR]

Air quality levels do not just affect climate change; rather, it leaves a significant impact on public health and wellbeing. Indoor air pollution is the major contributor to increased mortality and morbidity rates. This paper is focused on the assessment of indoor air quality based on several important pollutants (PM10, PM2.5, CO2, CO, tVOC, and NO2). These pollutants are responsible for potential health issues, including respiratory disease, central nervous system dysfunction, cardiovascular disease, and cancer. The pollutant concentrations were measured from a rural site in India using an Internet of Things-based sensor system. An Adaptive Dynamic Fuzzy Inference System Tree was implemented to process the field variables. The knowledge base for the proposed model was designed using a global optimization algorithm. However, the model was tuned using a local search algorithm to achieve enhanced prediction performance. The proposed model gives normalized root mean square error of 0.6679, 0.6218, 0.1077, 0.2585, 0.0667 and 0.0635 for PM10, PM2.5, CO2, CO, tVOC, and NO2, respectively. This approach was compared with the existing studies in the literature, and the approach was also validated against the online benchmark dataset. [ABSTRACT FROM AUTHOR]

Eutrophication has emerged as one of the main threats to surface water bodies. The parameters for assessing eutrophication are not generally measured regularly from the lakes of India as part of monitoring programmes and it is necessary to express the trophic status in terms of secondary indicator variables that are included in the routine analysis by the State/Central government. In this paper, the trophic status of Ashtamudi Lake has been studied, considering its international importance and socio-economic relevance. The cause and response variables such as total phosphorus, Secchi disc depth, chlorophyll-a and the secondary indicator variables such as pH, turbidity, DO, EC, Salinity, TDS and BOD were analysed during the pre-monsoon season. The lake was predominantly classified as eutrophic, with some areas coming under a hypereutrophic state. A comparison was made among the five methods of water quality index by the use of secondary indicator variables to identify the appropriate method for simulating trophic status and the WQI based on the logarithmic method considering pH, turbidity, DO and BOD was identified to predict the trophic state very well. Further, the application of numerical strategy such as fuzzy logic was used to determine water quality indexes and trophic status, which can define the quality of a water body as a consequence of the variation of environmental parameters. The developed approach was further validated by using historical data for the years 2013–2015, which were regularly monitored by the Kerala State Pollution Control Board. The trophic state predicted by the approach was found to be in agreement with that estimated using Carlson's method. Thus the developed model, based on secondary indicator parameters that are readily available from government agencies, can be used to assess the trophic state of lakes, thereby assisting policy makers to frame regulations to minimize eutrophication. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 had already shown its harmful impact on mankind, especially on health sectors, global economy, education systems, cultures, politics, and other important fields. Like most of the affected countries in the globe, India is now facing serious crisis due to COVID-19 in the recent times. The evaluation of the present status of the provinces affected by COVID-19 is very much essential to the government authorities to impose preventive strategies in controlling the spread of COVID-19 and to take necessary measures. In this article, a computational methodology is developed to estimate the present status of states and provinces which are affected due to COVID-19 using a fuzzy inference system. The factors such as population density, number of COVID-19 tests, confirmed cases of COVID-19, recovery rate, and mortality rate are considered as the input parameters of the proposed methodology. Considering positive and negative factors of the input parameters, the rule base is developed using triangular fuzzy numbers to capture uncertainties associated with the model. The application potentiality is validated by evaluating Pearson's correlation coefficient. A sensitivity analysis is also performed to observe the changes of final output by varying the tolerance ranges of the inputs. The results of the proposed method show that some of the provinces have very poor performance in controlling the spread of COVID-19 in India. So, the government needs to take serious attention to deal with the pandemic situation of COVID-19 in those provinces. [Display omitted] • Provinces' performance to control spread of COVID-19 is assessed using fuzzy system. • Factors influencing COVID-19 are identified and considered as inputs. • Starting of government and non-government services for public can be identified. • Role models in taking preventive strategies against COVID-19 pandemic can be traced. • Equitable distribution strategies of COVID-19 vaccines can be made. [ABSTRACT FROM AUTHOR]