Faculty Publications

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Subject: search.filters.subject.Sensitivity analysis

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    Crop classification using gene expression programming technique
    (Springer Verlag service@springer.de, 2013) Narasipura, O.S.; John, R.L.; Choudhry, N.; Kubusada, Y.; Bhageshpur, G.
    Precise classification of agricultural crops provides vital information on the type and extent of crops cultivated in a particular area. This information plays an important role in planning further cultivation activities. Image classification forms the core of the solution to the crop coverage identification problem. In this paper we present the experimental results obtained by using Gene Expression Programming (GEP) to classify the crop data obtained from satellite images. We have adopted supervised one-against-all learning technique to perform the classification of data. Gene Expression Programming provides an efficient method for obtaining classification rules in the form of a mathematical expression for a given data set containing input and output variables. We have also compared the classification efficiencies obtained with those of other classifiers namely Support vector machines and Artificial neural networks. Sensitivity Analysis has also been carried out to determine the significance of each input variable. © 2013 Springer-Verlag.
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    A gene expression based quality of service aware routing protocol for mobile ad hoc networks
    (2013) Kubusada, Y.; Mohan, G.; Manjappa, M.; Guddeti, G.
    Mobile Ad Hoc Network (MANET) is a collection of infrastructure less multi-hop wireless mobile nodes which communicate together to achieve the global task. Despite lack of centralized control these mobile nodes still coordinate together to deliver the message to the destination node. MANET is gaining its popularity due to its easy deployment and self-organizing ability. In spite of its unique characteristics, mobility of mobile nodes causes frequent link breakups in MANET and thus makes route setup and maintenance a critical and challenging task. As real time and multimedia applications are increasing, there is a need of an efficient Quality of Service (QoS) aware routing protocol for MANET to support such applications. In the present work, the authors proposed an efficient QoS aware routing protocol for MANET based on upcoming Gene Expression Programming. In the proposed work, the information regarding the availability of resources is managed by a resource management module, which assists in selecting the resource rich path. Further, a theoretical proof is given for the proposed model for its correctness. The results are compared with the state of art artificial neural network and support vector regression methods from the performance evaluation point of view and the results are encouraging. © 2013 Springer Science+Business Media.
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    Intelligent Modeling for Shear Strength of RC Exterior Beam-Column Joint Subjected to Seismic Loading
    (Springer Science and Business Media Deutschland GmbH, 2023) Swapnil, B.; Palanisamy, T.
    RC beam-column joints are subjected to impounding shear demand and bond-slip during the event of an earthquake. Accurate prediction of joint shear strength is necessary to avoid brittle shear failure in design and retrofitting procedures. In this study the accurate shear strength of RC exterior beam-column joints are predicted by providing a contemporary intelligent modeling approach through eXtreme Gradient Boosting regressor (XGBoost), an ensemble learning technique that combines several weak learners to generate a strong predictive model. From the experimental results of diverse publications on exterior beam-column joints, parameters affecting joint shear strength are found through examination of current models, and a vast database is constructed. Eleven such parameters that describe the material property, geometric configuration and bond resistance, are chosen as the inputs, and joint shear strength as the output. The model is then trained, tested and validated on this database. The performance of this model is evaluated by various regression evaluation metrics such as MSE, RMSE, and R2. Comparison of this model with the existing empirical equation, code provisions, and even with an individual ML algorithm, demonstrated its superiority over all the models in terms of accuracy and computation time. Sensitivity analysis done using predictive power score (PPS) showed that the most important parameter for the estimation of the shear strength of RC exterior beam-column joint is the percentage of beam longitudinal reinforcement. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Predicting the Axial Load Carrying Capacity of Columns Reinforced with GFRP Rebars Using ANN Modelling
    (Springer Science and Business Media Deutschland GmbH, 2023) Sumesh Manohar, G.; Palanisamy, T.
    In recent years most of the concrete structures are getting exposed to environments that are resulting in the corrosion of steel. To eliminate this, studies have been carried out to replace steel in RCC by Glass Fiber Reinforced Polymer (GFRP) rebars. In this paper, several experimental results were considered and the impacts of substituting steel by GFRP rebars were studied. Parameters affecting the load-carrying capacity of columns reinforced with GFRP rebars were identified from various literature and a database has been created. Twelve such parameters describing the material property and geometric configuration are chosen as inputs and the axial load carrying capacity as an output. An ANN model is developed with optimized architecture for predicting the compressive strength of columns reinforced with GFRP rebars. The model is then trained, tested, and validated on this database. The accuracy of the ANN model is evaluated by various regression evaluation metrics such as MSE, RMSE and R2. Comparison with the existing empirical equations and code provisions showed that the ANN model outperformed all these models. For the purpose of determining the efficiency of ANN model, a subset of the experimental data collected from work done on GFRP reinforced columns is used. Sensitivity analysis is carried out and the results showed that the most important parameters for the estimation of the strength of GFRP reinforced columns are the geometrical dimensions of the column. The results obtained showed that the ANN model is in good agreement with the experimental results. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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    Adaptive Neuro-Fuzzy Systems and Ensemble Methods in Joint Shear Prediction and Sensitivity Analysis
    (Springer Science and Business Media Deutschland GmbH, 2024) Palkar, S.S.; Palanisamy, T.
    In the absence of ductile design, beam-column joints form weak links in the frame during seismic activities, hence jeopardizing the entire structure. Deducing from the views of researchers, estimation of joint shear strength of RC beam-column joint is a necessity with a complexity. This complexity highlights the importance of machine learning models due to their data handling and predictive capabilities. This study used 233 beam-column joints with 132 exterior and 101 interior joints for training and testing the ensemble machine-learning models and an Adaptive neuro-fuzzy inference system. The performance indices of the models built and their comparison is carried out to find the optimum model to be deployed. The sensitivity analysis of the features considered was conducted to infer the differences in exterior and interior beam-column joints’ behavior. © 2023, Springer Science and Business Media Deutschland GmbH. All rights reserved.
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    Toward Selection and Improving the Performance of the SWAT Hydrological Model: A Review
    (Springer Science and Business Media Deutschland GmbH, 2024) Yashas Kumar, H.K.Y.; Kumble, V.
    In watershed hydrology, it is challenging to physically monitor various aspects that influence the hydrological processes. To quantify these watershed processes in a basin with changing spatial and temporal characteristics, public domain hydrological models incorporating inverse modeling are considered. The quantified processes aid in the decision-making, design, and development of hydrological units. But the first confusion that arises in modeling these processes is which hydrological model should be considered and what methods should be adopted to quantify the best hydrological parameters. Even though a best model is considered hydrologists assumption of parameter insensitivity and uniqueness over varying climatic conditions and space, the conditionality of model calibration with unique technique and performance indicator is prone to the poor performance of the model. Betterment of model performance can be achieved by switching parameters sensitive to varying climatic conditions and reprieving the conditionality of model calibration. Hence, the purpose of this paper is to review (i) different hydrological models available around the globe, (ii) the selection criteria for the hydrological model and the superiority of the SWAT model, (iii) the description of the SWAT model, followed by sensitivity analysis and calibration techniques involved in SWAT output, and (iv) summaries of season-based SWAT evaluation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
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    Coordinated voltage control using multiple regulators in distribution system with distributed generators
    (2011) Shivarudraswamy, R.; Gaonkar, D.N.
    The continued interest in the use of distributed generation in recent years is leading to the growth in number of distributed generators connected to distribution networks. Steady state voltage rise resulting from the connection of these generators can be a major obstacle to their connection at lower voltage levels. The present electric distribution network is designed to keep the customer voltage within tolerance limit. This may require a reduction in connectable generation capacity, under utilization of appropriate generation sites. Thus distribution network operators need a proper voltage regulation method to allow the significant integration of distributed generation systems to existing network. In this work a voltage rise problem in a typical distribution system has been studied. A method for voltage regulation of distribution system with multiple DG system by coordinated operation distributed generator, capacitor and OLTC has been developed. A sensitivity based analysis has been carried out to determine the priority for individual generators in multiple DG environment. The effectiveness of the developed method has been evaluated under various cases through simulation results.
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    Coordinated voltage control using multiple regulators in distribution system with distributed generators
    (2011) Shivarudraswamy, R.; Gaonkar, D.N.
    The continued interest in the use of distributed generation in recent years is leading to the growth in number of distributed generators connected to distribution networks. Steady state voltage rise resulting from the connection of these generators can be a major obstacle to their connection at lower voltage levels. The present electric distribution network is designed to keep the customer voltage within tolerance limit. This may require a reduction in connectable generation capacity, under utilization of appropriate generation sites. Thus distribution network operators need a proper voltage regulation method to allow the significant integration of distributed generation systems to existing network. In this work a voltage rise problem in a typical distribution system has been studied. A method for voltage regulation of distribution system with multiple DG system by coordinated operation distributed generator, capacitor and OLTC has been developed. A sensitivity based analysis has been carried out to determine the priority for individual generators in multiple DG environment. The effectiveness of the developed method has been evaluated under various cases through simulation results.
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    Sensitivity of Pushover Curve to Material and Geometric Modelling-An Analytical Investigation
    (Elsevier Ltd, 2015) Panandikar, N.; Babu Narayan, K.S.
    Nonlinear static analysis or pushover analysis developed over the last two decades and became the preferred procedure for design and seismic performance evaluation, as this procedure is relatively simple and considers post-elastic behaviour. It provides information on seismic demands imposed by the design ground motion on the structural system and its components. Generation of pushover curve from analysis for reinforced concrete structure involves tremendous amount of computational efforts as the input data for analysis itself is quite exhaustive. The analysis results are very sensitive to the techniques employed in geometric and material modelling. This paper envisages presenting the sensitivity of pushover analysis results to geometric and material modelling parameters by comparing the analysis results with that of experimental investigations. Attempt has been made to understand the sensitivity of parameters like variation in material properties, inaccuracies in placement of reinforcement, effect of confinement of concrete and modelling techniques for elements and plastic hinges. SAP-2000 has been utilised in the current investigation and results have been highlighted suggesting strategies to enhance pushover analysis capabilities. © 2015 Elsevier B.V.
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    Streamflow response to land use-land cover change over the Nethravathi River Basin, India
    (American Society of Civil Engineers (ASCE), 2015) Babar, S.; Ramesh, H.
    Land use-land cover change (LULC) has considerable impacts on hydrologic response at the watershed level. Quantitative assessment of LULC impacts on runoff generations is vital for water resources development. The soil and water assessment tool (SWAT) model was used to study the effect of LULC change on streamflows. In addition to this, the present study proposed a newly developed flow-routing model called runoff coefficient routing model (RCRM). This new model is simple and requires limited data, such as precipitation, LULC and streamflows as compared to other models, which require meteorological and many more input data. The Nethravathi River basin was selected for testing the RCRM model with the SWAT model to study land use-land cover change on streamflows. The SWAT model and RCRM model have been calibrated for 2001-2005 and validated for 2006-2009 daily data. Results have shown that the simulated streams are well correlated with observed streamflows with a coefficient of correlation (R2) equal to 0.82 in calibration and 0.68 in validation period. Whereas, the RCRM model results have shown R2 of 0.81 and 0.66 in the calibration and validation period. Finally, the SWAT and RCRM results were compared. It is observed that the results of the RCRM model have shown a good agreement with SWAT model results of R2 equal to 0.99 and 0.98, respectively, in the calibration and validation period. The sensitivity analysis was also carried out based on Latin hypercube one factor-at-a-time (LH-OAT) method using the SWAT model and found 11 sensitive parameters out of 28 parameters. Model performance was carried out using the Nash-Sutcliffe model efficiency coefficient (NSE) and found 0.81 for calibration and 0.62 for the validation period in the SWAT model. RCRM has NSE of 0.79 and 0.63. The response of the streamflows for the year 2013 was simulated from the calibrated model. The results showed that the observed streamflows have shown good correlation with simulated streamflows with R2 values of 0.86 and NSE of 0.81. From the results, it is concluded that the runoff shows early response in the year 2013 compared to the year 2003. This is mainly due to changes in LULC, which shows the conversion of forest to agricultural area and increase in built-up area from 2003 to 2013. The effect of LULC change on the hydrological model parameters were calculated and observed a decrease in evapotranspiration (ET) of about 4.5%, an increase in runoff of about 0.9%, and an increase in groundwater of about 1.12%. In conclusion, the proposed RCRM in the present study simulates streamflows at par with the SWAT model with only few input data. Hence, the newly developed RCRM model would be used to study streamflows responses to LULC changes. © 2015 American Society of Civil Engineers.