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AI-Based Hybrid Models for Predicting Loan Risk in the Banking Sector

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Big Data Mining and Analytics 2023年第4期6卷 478-490页

作者： Vikas kumar Shaiku Shahida Saheb Preeti Atif Ghayas Sunil kumari Jai Kishan Chandel saroj kumar pandey Santosh kumar Humanities and Management Department Dr.B.R.Ambedkar National Institute of Technology JalandharJalandhar 144027India. Mittal School of Business Lovely Professional UniversityPhagwara 144402India. Department of Commerce&Business Administration Kanya Maha Vidyalaya(KMV)Jalandhar 144004India School of Management Gitam(to be deemed university)Bangalore 561203India Government College for Women Indra Gandhi UniversityAteli 123021India. Institute of Management Studies Kurukshetra UniversityKurukshetra 136119India Department of Computer Engineering and Applications GLA UniversityMathura 281406India Department of Management Jaipuriya Institute of ManagementJaipur 302033India

Every real-world scenario is now digitally replicated in order to reduce paperwork and human labor *** Learning(ML)models are also being used to make predictions in these *** forecasting requires knowledge of these machine learning models and their distinguishing *** datasets we use as input for each of these different types of ML models,yielding different *** choice of an ML model for a dataset is critical.A loan risk model is used to show how ML models for a dataset can be linked *** purpose of this study is to look into how we could use machine learning to quantify or forecast mortgage credit *** phrase refers to the process of evaluating massive amounts of data in order to derive useful information for making decisions in a variety of *** credit risk is considered,a method based on an examination of what caused and how mortgage credit risk affected credit defaults during the still-current economic crisis of 2021 will be *** approaches to credit risk calculation will be examined,ranging from the most basic to the most *** addition,we will conduct a case study on a sample of mortgage loans and compare the results of three different analytical approaches,logistic regression,decision tree,and gradient boost to see which one produced the most commercially useful insights.

关键词： Artificial Intelligence(AI) Machine Learning(ML) loan prediction Support Vector Machine(SVM) Random Forest(RF) accuracy

A Hybrid Moth Flame Optimization Algorithm for Global Optimization

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Journal of Bionic Engineering 2022年第5期19卷 1522-1543页

作者： saroj kumar Sahoo Apu kumar Saha Department of Mathematics National Institute of TechnologyAgartalaTripura 799046India

The Moth Flame Optimization(MFO)algorithm shows decent performance results compared to other meta-heuristic algorithms for tackling non-linear constrained global optimization ***,it still suffers from obtaining quality solution and slow convergence *** the other hand,the Butterfly Optimization Algorithm(BOA)is a comparatively new algorithm which is gaining its popularity due to its simplicity,but it also suffers from poor exploitation *** this study,a novel hybrid algorithm,h-MFOBOA,is introduced,which integrates BOA with the MFO algorithm to overcome the shortcomings of both the algorithms and at the same time inherit their *** performance evaluation,the proposed h-MFOBOA algorithm is applied on 23 classical benchmark functions with varied *** tested results of the proposed algorithm are compared with some well-known traditional meta-heuristic algorithms as well as MFO *** rank test and Wilcoxon signed rank test are employed to measure the performance of the newly introduced algorithm *** computational complexity has been ***,the proposed algorithm has been applied to solve one constrained and one unconstrained real-life problems to examine its problem-solving capability of both type of *** comparison results of benchmark functions,statistical analysis,real-world problems confirm that the proposed h-MFOBOA algorithm provides superior results compared to the other conventional optimization algorithms.

关键词： Moth fame optimization algorithm Butterfly optimization algorithm Bio-inspired Benchmark functions Friedman rank test

A Novel Variant of Moth Flame Optimizer for Higher Dimensional Optimization Problems

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Journal of Bionic Engineering 2023年第5期20卷 2389-2415页

作者： saroj kumar Sahoo Sushmita Sharma Apu kumar Saha Department of Mathematics National Institute of Technology AgartalaJiraniaTripura799046India

Moth Flame Optimization(MFO)is a nature-inspired optimization algorithm,based on the principle of navigation technique of moth toward *** to less parameter and easy implementation,MFO is used in various field to solve optimization ***,for the complex higher dimensional problems,MFO is unable to make a good trade-off between global and local *** overcome these drawbacks of MFO,in this work,an enhanced MFO,namely WF-MFO,is introduced to solve higher dimensional optimization *** a more optimal balance between global and local search,the original MFO’s exploration ability is improved by an exploration operator,namely,Weibull flight *** addition,the local optimal solutions have been avoided and the convergence speed has been increased using a Fibonacci search process-based technique that improves the quality of the solutions ***-nine benchmark functions of varying complexity with 1000 and 2000 dimensions have been utilized to verify the projected *** popular algorithms and MFO versions have been compared to the achieved *** addition,the robustness of the proposed WF-MFO method has been evaluated using the Friedman rank test,the Wilcoxon rank test,and convergence *** to other methods,the proposed WF-MFO algorithm provides higher quality solutions and converges more quickly,as shown by the ***,the proposed WF-MFO has been used to the solution of two engineering design issues,with striking *** improved performance of the proposed WF-MFO algorithm for addressing larger dimensional optimization problems is guaranteed by analyses of numerical data,statistical tests,and convergence performance.

关键词： Moth Flame Optimization(MFO)algorithm Bio-inspired algorithm Fibonacci search method Weibull distribution Higher dimensional functions

mLBOA:A Modified Butterfly Optimization Algorithm with Lagrange Interpolation for Global Optimization

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Journal of Bionic Engineering 2022年第4期19卷 1161-1176页

作者： Sushmita Sharma Sanjoy Chakraborty Apu kumar Saha Sukanta Nama saroj kumar Sahoo Department of Mathematics National Institute of Technology AgartalaAgartalaTripura 799046India Department of Computer Science and Engineering Iswar Chandra Vidyasagar CollegeBeloniaTripura 799155India Department of Computer Science and Engineering National Institute of Technology AgartalaAgartalaTripura 799046India Department of Applied Mathematics Maharaja Bir Bikram UniversityAgartalaTripura 799004India

Though the Butterfly Bptimization Algorithm(BOA)has already proved its effectiveness as a robust optimization algorithm,it has certain ***,a new variant of BOA,namely mLBOA,is proposed here to improve its *** proposed algorithm employs a self-adaptive parameter setting,Lagrange interpolation formula,and a new local search strategy embedded with Levy flight search to enhance its searching ability to make a better trade-off between exploration and ***,the fragrance generation scheme of BOA is modified,which leads for exploring the domain effectively for better *** evaluate the performance,it has been applied to solve the IEEE CEC 2017 benchmark *** results have been compared to that of six state-of-the-art algorithms and five BOA ***,various statistical tests,such as the Friedman rank test,Wilcoxon rank test,convergence analysis,and complexity analysis,have been conducted to justify the rank,significance,and complexity of the proposed ***,the mLBOA has been applied to solve three real-world engineering design *** all the analyses,it has been found that the proposed mLBOA is a competitive algorithm compared to other popular state-of-the-art algorithms and BOA variants.

关键词： Butterfly optimization algorithm Lagrange interpolation Levy flight search IEEE CEC 2017 functions Engineering design problems

Comparative Performance Analysis of Differential Evolution Variants on Engineering Design Problems

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Journal of Bionic Engineering 2022年第4期19卷 1140-1160页

作者： Sanjoy Chakraborty Apu kumar Saha Sushmita Sharma saroj kumar Sahoo Gautam Pal Department of Computer Science and Engineering National Institute of Technology AgartalaAgartalaTripura 799046India Department of Computer Science and Engineering Iswar Chandra Vidyasagar CollegeBeloniaTripura 799155India Department of Mathematics National Institute of Technology AgartalaAgartalaTripura 799046India Department of Computer Science and Engineering Tripura Institute of TechnologyNarsingarhTripura 799015India

Because of their superior problem-solving ability,nature-inspired optimization algorithms are being regularly used in solving complex real-world optimization *** academics have recently focused on meta-heuristic algorithms to solve various optimization *** the state-of-the-art algorithms,Differential Evolution(DE)is one of the most successful algorithms and is frequently used to solve various industrial *** the previous 2 decades,DE has been heavily modified to improve its *** DE variations secured positions in IEEE CEC competitions,establishing their ***,to our knowledge,there has never been a comparison of performance across various CEC-winning DE versions,which could aid in determining which is the most *** this study,the performance of DE and its eight other IEEE CEC competition-winning variants are ***,the algorithms have evaluated IEEE CEC 2019 and 2020 bound-constrained functions,and the performances have been *** unconstrained problem from IEEE CEC 2011 problem suite and five other constrained mechanical engineering design problems,out of which four issues have been taken from IEEE CEC 2020 non-convex constrained optimization suite,have been solved to compare the *** analyses like Friedman's test and Wilcoxon's test are executed to verify the algorithm’s ability *** analysis exposes that none of the DE variants can solve all the problems *** of SHADE and ELSHADE-SPACMA are considerable among the methods used for comparison to solve such mechanical design problems.

关键词： Differential evolution Metaheuristics IEEE CEC Mechanical design problem

Effects of delay in immunological response of HIV infection

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International Journal of Biomathematics 2018年第6期11卷 1-29页

作者： saroj kumar Sahani Yashi Department of Mathematics South Asian University Akbar Bhawan Chankyapuri New Delhi 110021 India

In this paper, a human immunodeficiency virus (HIV) infection model with both the types of immune responses, the antibody and the killer cell immune responses has been introduced. The model has been made more logical by including two delays in the activation of both the immune responses, along with the combination drug therapy. The inclusion of both the delayed immune responses provides a greater understanding of long-term dynamics of the disease. The dependence of the stability of the steady states of the model on the reproduction number R 0 has been explored through stability theory. Moreover, the global stability analysis of the infection-free steady state and the infected steady state has been proved with respect to R 0 . The bifurcation analysis of the infected steady state with respect to both delays has been performed. Numerical simulations have been carried out to justify the results proved. This model is capable of explaining the long-term dynamics of HIV infection to a greater extent than that of the existing model as it captures some basic parameters involved in the system such as immunological delay and immune response. Similarly, the model also explains the basic understanding of the disease dynamics as a result of activation of the immune response toward the virus.

关键词：免疫学 HIV 感染延期反应稳定性理论免疫力稳定性分析

Study of Non-Pharmacological Interventions on COVID-19 Spread

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Computer Modeling in Engineering & Sciences 2020年第12期125卷 967-990页

作者： Avaneesh Singh saroj kumar Chandra Manish kumar Bajpai PDPM Indian Institute of Information Technology Design and ManufacturingJabalpur482005India

COVID-19 disease has emerged as one of the life threatening threat to the society.A novel beta coronavirus causes *** began as unidentified pneumonia of unknown etiology in Wuhan City,Hubei province in China emerged in December *** vaccine has been produced till *** models are used to study the impact of different measures used to decrease *** models have been designed to estimate the numbers of spreaders in different scenarios in the present *** the present manuscript,three different mathematical models have been proposed with different scenarios,such as screening,quarantine,andNPIs,to estimate the number of virus *** analysis shows that the numbers of COVID-19 patients will be more without screening the peoples coming from other *** every people suffering fromCOVID-19 disease are *** screening and quarantine with NPIs have been implemented to study their impact on the *** has been found that NPI measures can reduce the number of *** NPI measures reduce the spread function’s growth and provide decision makers more time to prepare with in dealing with the disease.

关键词： Coronavirus COVID-19 mathematical modelling epidemic

Phytohormones and their metabolic engineering for abiotic stress tolerance in crop plants

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The Crop Journal 2016年第3期4卷 162-176页

作者： Shabir H.Wani Vinay kumar Varsha Shriram saroj kumar Sah Division of Genetics and Plant Breeding Faculty of Agriculture WADURASher-e-Kashmir University of Agricultural Sciences and Technology Department of Biotechnology Modern College of ArtsScience and CommerceS.P.Pune University Department of Botany Prof.Ramkrishna More CollegeS.P.Pune University Department of Biochemistry Molecular BiologyEntomology and Plant PathologyMississippi State University

Abiotic stresses including drought,salinity,heat,cold,flooding,and ultraviolet radiation causes crop losses *** recent times,preventing these crop losses and producing more food and feed to meet the demands of ever-increasing human populations have gained unprecedented ***,the proportion of agricultural lands facing multiple abiotic stresses is expected only to rise under a changing global climate fueled by anthropogenic *** the mechanisms developed and deployed by plants to counteract abiotic stresses and maintain their growth and survival under harsh conditions thus holds great *** investigations have shown that phytohormones,including the classical auxins,cytokinins,ethylene,and gibberellins,and newer members including brassinosteroids,jasmonates,and strigolactones may prove to be important metabolic engineering targets for producing abiotic stress-tolerant crop *** this review,we summarize and critically assess the roles that phytohormones play in plant growth and development and abiotic stress tolerance,besides their engineering for conferring abiotic stress tolerance in transgenic *** also describe recent successes in identifying the roles of phytohormones under stressful *** conclude by describing the recent progress and future prospects including limitations and challenges of phytohormone engineering for inducing abiotic stress tolerance in crop plants.

关键词： Phytohormones Abiotic stress Metabolic engineering Plant stresses

Role of C-Peptide in Relation to Levels of Anti-GAD and Islet Cell Antibodies in Characterizing Types of Diabetes in the Young, in Eastern India

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Journal of Diabetes Mellitus 2022年第1期12卷 1-11页

作者： Sidhartha Das Dipanweeta Routray Manoranjan Behera saroj kumar Tripathy Formerly HOD P. G. Department of Medicine and Dean and Principal SCBMCH Cuttack India Department of Community Medicine SCBMCH Cuttack India SCBMCH Cuttack India Department of Department of Medicine. S. L. M. Medical College Koraput Odisha India

Background: Measuring fasting C-peptide (FCP) and antibodies against Glutamic acid decarboxylase (GADA) and Islet cell antibodies (ICA) are not so commonly explored in children and young adults. Objectives: To assess the levels of FCP, GADA and ICA in subjects below the age of 25 years with DM and compare their levels to differentiate between Autoimmune and Non-Autoimmune Type 1 DM. Methodology: Blood samples of 93 subjects diagnosed with DM, reporting to the tertiary care hospital, were analysed for ICA, GADA and FCP. Receiver operating characteristics (ROC) curves were analysed to check the ability of autoimmune markers, BMI and C-peptide to differentiate between Autoimmune (Ai) and Non-Autoimmune (NonAi) diabetes. Results: 30/93 (32.2%) were positive for anti-GAD ab and/or ICA and categorised as Autoimmune (Ai), the most common antibody being, anti-GAD ab (80%) in them. The level of FCP among Ai compared to NonAi, was significantly low (p 20.75 nmol/l) as a very dependable test for diagnosing Ai, Type 1 DM, in children and young adults. Its sensitivity and specificity are in the range of 86.2% and 96.8% respectively. Low level of C-peptide (Conclusion: This study revealed predominant positivity for anti-GAD ab (80%) among Ai+ patients. ROC analysis shows GADA above 20.75 nmol/l and Fasting C-peptide < 0.36 nmol/l as a good indicator for diagnosing Ai in children and young adults.

关键词： C-Peptide Anti-Glutamic Acid Decarboxylase Antibodies (GADA) Islet Cell Antibodies (ICA) ROC Analysis Type 1 DM Type 2 DM