Ch. Sanjeev Kumar Dash

518 total citations · 1 hit paper
15 papers, 264 citations indexed

About

Ch. Sanjeev Kumar Dash is a scholar working on Artificial Intelligence, Computer Networks and Communications and Control and Systems Engineering. According to data from OpenAlex, Ch. Sanjeev Kumar Dash has authored 15 papers receiving a total of 264 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 2 papers in Computer Networks and Communications and 2 papers in Control and Systems Engineering. Recurrent topics in Ch. Sanjeev Kumar Dash's work include Neural Networks and Applications (6 papers), Metaheuristic Optimization Algorithms Research (3 papers) and Imbalanced Data Classification Techniques (3 papers). Ch. Sanjeev Kumar Dash is often cited by papers focused on Neural Networks and Applications (6 papers), Metaheuristic Optimization Algorithms Research (3 papers) and Imbalanced Data Classification Techniques (3 papers). Ch. Sanjeev Kumar Dash collaborates with scholars based in South Korea, India and United States. Ch. Sanjeev Kumar Dash's co-authors include Satchidananda Dehuri, Ajit Kumar Behera, Ashish Ghosh, Sung‐Bae Cho, Sung-Bae Cho, Sarat Chandra Nayak, Gi-Nam Wang, Rajib Mall, Mrutyunjaya Panda and Jnyana Ranjan Mohanty and has published in prestigious journals such as Pattern Recognition Letters, Engineering Applications of Artificial Intelligence and International Journal of Computational Intelligence Systems.

In The Last Decade

Ch. Sanjeev Kumar Dash

15 papers receiving 249 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

An outliers detection and elimination framework in classification task of data mining

2023 114 citations Ch. Sanjeev Kumar Dash, Ajit Kumar Behera et al. Decision Analytics Journal profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ch. Sanjeev Kumar Dash South Korea	7	94	29	25	24	21	15	264
Jojo Moolayil	4	77 0.8×	33 1.1×	36 1.4×	15 0.6×	22 1.0×	4	251
Vatsal Patel India	4	72 0.8×	23 0.8×	25 1.0×	18 0.8×	16 0.8×	9	312
Mahmoud Reza Saybani Malaysia	7	88 0.9×	59 2.0×	28 1.1×	19 0.8×	9 0.4×	14	253
Sarbartha Sarkar India	7	95 1.0×	38 1.3×	51 2.0×	24 1.0×	23 1.1×	8	355
Yashuang Mu China	8	139 1.5×	47 1.6×	18 0.7×	25 1.0×	29 1.4×	25	438
Mengxiang Chen China	7	154 1.6×	42 1.4×	21 0.8×	17 0.7×	32 1.5×	17	337
Salih Sarp United States	10	162 1.7×	47 1.6×	31 1.2×	13 0.5×	15 0.7×	23	322
Yevgeniya Kovalchuk United Kingdom	9	101 1.1×	26 0.9×	19 0.8×	21 0.9×	15 0.7×	27	334
Zhang Min China	4	50 0.5×	50 1.7×	30 1.2×	12 0.5×	17 0.8×	7	262

Countries citing papers authored by Ch. Sanjeev Kumar Dash

Since Specialization

Citations

This map shows the geographic impact of Ch. Sanjeev Kumar Dash's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ch. Sanjeev Kumar Dash with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ch. Sanjeev Kumar Dash more than expected).

Fields of papers citing papers by Ch. Sanjeev Kumar Dash

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ch. Sanjeev Kumar Dash. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ch. Sanjeev Kumar Dash. The network helps show where Ch. Sanjeev Kumar Dash may publish in the future.

Co-authorship network of co-authors of Ch. Sanjeev Kumar Dash

This figure shows the co-authorship network connecting the top 25 collaborators of Ch. Sanjeev Kumar Dash. A scholar is included among the top collaborators of Ch. Sanjeev Kumar Dash based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ch. Sanjeev Kumar Dash. Ch. Sanjeev Kumar Dash is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

Dash, Ch. Sanjeev Kumar, Ajit Kumar Behera, Satchidananda Dehuri, & Ashish Ghosh. (2023). An outliers detection and elimination framework in classification task of data mining. Decision Analytics Journal. 6. 100164–100164. 114 indexed citations breakdown →

Mohanty, Jnyana Ranjan, et al.. (2022). Effort Estimation of Software products by using UML Sequence models with Regression Analysis. 97–101. 1 indexed citations

Behera, Ajit Kumar, Ch. Sanjeev Kumar Dash, Mrutyunjaya Panda, Satchidananda Dehuri, & Rajib Mall. (2021). A state-of-the-art neuro-swarm approach for prediction of software reliability. International Journal of Advanced Intelligence Paradigms. 20(3/4). 296–296. 1 indexed citations

Nayak, Sarat Chandra, et al.. (2021). A machine learning approach for estimating compressive strength of concrete structures using an artificial electric field algorithm-based neuro-fuzzy predictor. 4 indexed citations

Behera, Ajit Kumar, et al.. (2021). Extreme Gradient Boosting and Soft Voting Ensemble Classifier for Diabetes Prediction. 191–195. 10 indexed citations

Dash, Ch. Sanjeev Kumar, Ajit Kumar Behera, Sarat Chandra Nayak, & Satchidananda Dehuri. (2021). QORA-ANN: Quasi Opposition Based Rao Algorithm and Artificial Neural Network for Cryptocurrency Prediction. 6 indexed citations

Dash, Ch. Sanjeev Kumar, Ajit Kumar Behera, Sarat Chandra Nayak, Satchidananda Dehuri, & Sung-Bae Cho. (2019). An Integrated CRO and FLANN Based Classifier for a Non-Imputed and Inconsistent Dataset. International Journal of Artificial Intelligence Tools. 28(3). 1950013–1950013. 5 indexed citations

Dash, Ch. Sanjeev Kumar, Ajit Kumar Behera, Satchidananda Dehuri, & Sung-Bae Cho. (2019). Building a novel classifier based on teaching learning based optimization and radial basis function neural networks for non-imputed database with irrelevant features. Applied Computing and Informatics. 18(1/2). 151–162. 9 indexed citations

Dash, Ch. Sanjeev Kumar, et al.. (2016). Design of self-adaptive and equilibrium differential evolution optimized radial basis function neural network classifier for imputed database. Pattern Recognition Letters. 80. 76–83. 13 indexed citations

10.

Dash, Ch. Sanjeev Kumar, Ajit Kumar Behera, Satchidananda Dehuri, & Sung‐Bae Cho. (2016). Radial basis function neural networks: a topical state-of-the-artsurvey. Open Computer Science. 6(1). 33–63. 70 indexed citations

11.

Dash, Ch. Sanjeev Kumar, Ajit Kumar Behera, Satchidananda Dehuri, Sung‐Bae Cho, & Gi-Nam Wang. (2015). Towards crafting an improved functional link artificial neural network based on differential evolution and feature selection. Informatica (slovenia). 39(2). 195–208. 3 indexed citations

12.

Dash, Ch. Sanjeev Kumar, et al.. (2015). An Empirical Analysis of Evolved Radial Basis Function Networks and Support Vector Machines with Mixture of Kernels. International Journal of Artificial Intelligence Tools. 24(4). 1550013–1550013. 8 indexed citations

13.

Dash, Ch. Sanjeev Kumar, et al.. (2015). Towards Crafting a Smooth and Accurate Functional Link Artificial Neural Networks Based on Differential Evolution and Feature Selection for Noisy Database. International Journal of Computational Intelligence Systems. 8(3). 539–539. 4 indexed citations

14.

Behera, Ajit Kumar, et al.. (2013). On the study of GRBF and polynomial kernel based support vector machine in web logs. 1–5. 5 indexed citations

15.

Dash, Ch. Sanjeev Kumar, et al.. (2013). DE+RBFNs based classification: A special attention to removal of inconsistency and irrelevant features. Engineering Applications of Artificial Intelligence. 26(10). 2315–2326. 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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