An evaluation system for cloud service selection using fuzzy AHP. - Rakesh Ranjan Kumar; Chiranjeev Kumar (ICIIS, 2016)

Designing an efficient methodology based on Entropy-TOPSIS for evaluating efficiency of cloud services. - Rakesh Ranjan Kumar; Chiranjeev Kumar (ICCCT, 2017)

Prioritizing the solution of cloud service selection using integrated MCDM methods under Fuzzy environment. - Rakesh Ranjan Kumar; Siba Mishra; Chiranjeev Kumar (J. Supercomput., 2017)

A novel approach for cloud service composition ensuring global QoS constraints optimization. - Rashda Khanam; Rakesh Ranjan Kumar; Binita Kumari (ICACCI, 2018)

QoS based cloud service composition with optimal set of services using PSO. - Rashda Khanam; Rakesh Ranjan Kumar; Chiranjeev Kumar (RAIT, 2018)

A Multi Criteria Decision Making Method for Cloud Service Selection and Ranking. - Rakesh Ranjan Kumar; Chiranjeev Kumar (Int. J. Ambient Comput. Intell., 2018)

Prioritizing challenges of agile process in distributed software development environment using analytic hierarchy process. - Mohammad Shameem; Rakesh Ranjan Kumar; Chiranjeev Kumar; Bibhas Chandra; Arif Ali Khan (J. Softw. Evol. Process., 2018)

Fuzzy AHP based prioritization and taxonomy of software process improvement success factors in global software development. - Arif Ali Khan; Mohammad Shameem; Rakesh Ranjan Kumar; Shahid Hussain 001; Xuefeng Yan (Appl. Soft Comput., 2019)

Taxonomical classification of barriers for scaling agile methods in global software development environment using fuzzy analytic hierarchy process. - Mohammad Shameem; Rakesh Ranjan Kumar; Mohammad Nadeem; Arif Ali Khan (Appl. Soft Comput., 2020)

CCS-OSSR: A framework based on Hybrid MCDM for Optimal Service Selection and Ranking of Cloud Computing Services. - Rakesh Ranjan Kumar; Binita Kumari; Chiranjeev Kumar (Clust. Comput., 2021)

Developing a Cloud Intrusion Detection System with Filter-Based Features Selection Techniques and SVM Classifier. - Mhamad Bakro; Rakesh Ranjan Kumar; Sukant K. Bisoy; Mohammad Osama Addas; Dania Khamis (CoCoLe, 2022)

Sub-10 kHz Intrinsic Linewidth Extended Cavity DBR laser on InP Generic Foundry Platform. - Rakesh Ranjan Kumar; Andreas Hänsel; Mónica Brusatori Far; Lars Nielsen; Niklas Hedegaard Arent; Nicolas Volet; Martijn J. R. Heck (OFC, 2022)

A computational framework for ranking prediction of cloud services under fuzzy environment. - Rakesh Ranjan Kumar; Mohammad Shameem; Chiranjeev Kumar (Enterp. Inf. Syst., 2022)

Nearest Neighbor and Decision Tree Based Cloud Service QoS Classification. - Soumya Snigdha Mohapatra; Rakesh Ranjan Kumar; Sujit Bebortta (CoCoLe, 2023)

An Improved Design for a Cloud Intrusion Detection System Using Hybrid Features Selection Approach With ML Classifier. - Mhamad Bakro; Rakesh Ranjan Kumar; Amerah A. Alabrah; Zubair Ashraf; Mohammad Nadeem Ahmed; Mohammad Shameem; Ahmed Abdelsalam (IEEE Access, 2023)

Decision making for cloud service selection: a novel and hybrid MCDM approach. - Abhinav Tomar; Rakesh Ranjan Kumar; Indrajeet Gupta (Clust. Comput., 2023)

Building a Cloud-IDS by Hybrid Bio-Inspired Feature Selection Algorithms Along With Random Forest Model. - Mhamad Bakro; Rakesh Ranjan Kumar; Mohammad Husain; Zubair Ashraf; Arshad Ali 001; Syed Irfan Yaqoob; Mohammad Nadeem Ahmed; Nikhat Parveen (IEEE Access, 2024)

Refined Software Defect Prediction Using Enhanced JAYA Optimization and Extreme Learning Machine. - Debasish Pradhan; Debendra Muduli; Abu Taha Zamani; Syed Irfan Yaqoob; Sultan Munadi Alanazi; Rakesh Ranjan Kumar; Nikhat Parveen; Mohammad Shameem (IEEE Access, 2024)

An evolutionary supply chain management service model based on deep learning features for automated glaucoma detection using fundus images. - Santosh Kumar Sharma; Debendra Muduli; Rojalina Priyadarshini; Rakesh Ranjan Kumar; Abhinav Kumar 005; Jitesh Pradhan (Eng. Appl. Artif. Intell., 2024)

Towards Perpetual Wireless Rechargeable Sensor Networks with Path Optimization of Mobile Chargers. - Binita Kumari; Ajay Kumar Yadav; Rakesh Ranjan Kumar (SN Comput. Sci., 2024)

An empirical evaluation of extreme learning machine uncertainty quantification for automated breast cancer detection. - Debendra Muduli; Rakesh Ranjan Kumar; Jitesh Pradhan; Abhinav Kumar 005 (Neural Comput. Appl., 2025)