Kanchan Sinha

769 total citations · 1 hit paper
31 papers, 580 citations indexed

About

Kanchan Sinha is a scholar working on Management Science and Operations Research, General Agricultural and Biological Sciences and Economics and Econometrics. According to data from OpenAlex, Kanchan Sinha has authored 31 papers receiving a total of 580 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Management Science and Operations Research, 9 papers in General Agricultural and Biological Sciences and 7 papers in Economics and Econometrics. Recurrent topics in Kanchan Sinha's work include Forecasting Techniques and Applications (8 papers), Agricultural Economics and Practices (8 papers) and Stock Market Forecasting Methods (7 papers). Kanchan Sinha is often cited by papers focused on Forecasting Techniques and Applications (8 papers), Agricultural Economics and Practices (8 papers) and Stock Market Forecasting Methods (7 papers). Kanchan Sinha collaborates with scholars based in India and United Kingdom. Kanchan Sinha's co-authors include Goutam Kumar Ghosh, Shaon Kumar Das, R. K. Avasthe, Girish Kumar Jha, Ravikant Avasthe, Santosha Rathod, Mrinmoy Ray, Kehar Singh, Ranjit Kumar Paul and Anirban Mukherjee and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Hazardous Materials and Journal of Environmental Management.

In The Last Decade

Kanchan Sinha

30 papers receiving 560 citations

Hit Papers

Compositional heterogeneity of different biochar: Effect ... 2020 2026 2022 2024 2020 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kanchan Sinha India 10 121 101 100 91 76 31 580
Reza Abdi Iran 9 15 0.1× 67 0.7× 50 0.5× 134 1.5× 48 0.6× 13 490
Kapil Kumar India 15 108 0.9× 12 0.1× 102 1.0× 119 1.3× 277 3.6× 33 974
Andi Mehmeti Italy 16 37 0.3× 27 0.3× 85 0.8× 61 0.7× 107 1.4× 30 842
Hussnain Mukhtar Taiwan 14 78 0.6× 10 0.1× 90 0.9× 70 0.8× 107 1.4× 32 827
Mohd Armi Abu Samah Malaysia 12 24 0.2× 21 0.2× 111 1.1× 75 0.8× 402 5.3× 58 844
Morteza Almassi Iran 13 33 0.3× 53 0.5× 19 0.2× 237 2.6× 9 0.1× 52 697
Bernard Fei‐Baffoe Ghana 17 58 0.5× 15 0.1× 77 0.8× 69 0.8× 505 6.6× 59 1.1k
Ehsan Houshyar Iran 15 65 0.5× 88 0.9× 41 0.4× 31 0.3× 15 0.2× 30 632
Róbert Zeman Czechia 8 30 0.2× 8 0.1× 36 0.4× 116 1.3× 63 0.8× 13 432

Countries citing papers authored by Kanchan Sinha

Since Specialization
Citations

This map shows the geographic impact of Kanchan Sinha'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 Kanchan Sinha with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kanchan Sinha more than expected).

Fields of papers citing papers by Kanchan Sinha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kanchan Sinha. 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 Kanchan Sinha. The network helps show where Kanchan Sinha may publish in the future.

Co-authorship network of co-authors of Kanchan Sinha

This figure shows the co-authorship network connecting the top 25 collaborators of Kanchan Sinha. A scholar is included among the top collaborators of Kanchan Sinha 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 Kanchan Sinha. Kanchan Sinha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Sinha, Kanchan, et al.. (2023). Price volatility spillover of Indian onion markets: A comparative study. SHILAP Revista de lepidopterología. 88(1). 114–120. 3 indexed citations
3.
Ray, Mrinmoy, et al.. (2023). Rainfall prediction using time-delay wavelet neural network (TDWNN) model for assessing agrometeorological risk. Journal of Agrometeorology. 25(1). 1 indexed citations
4.
Mandal, Biswapati, Dibyendu Sarkar, Arup Chattopadhyay, et al.. (2022). Zinc and Iron Profiling in Some Commonly Consumed Food Crops Uncovers Inter- and Intra-crop Variation. Journal of soil science and plant nutrition. 22(2). 1768–1777. 1 indexed citations
5.
Das, Shaon Kumar, Goutam Kumar Ghosh, Ravikant Avasthe, & Kanchan Sinha. (2020). Morpho-mineralogical exploration of crop, weed and tree derived biochar. Journal of Hazardous Materials. 407. 124370–124370. 52 indexed citations
6.
Dey, Soumik, et al.. (2020). A Study on Academic Attainment of Agriculture Students and its Correlates: A Dummy Regression Approach. Annals of Data Science. 10(1). 129–152. 1 indexed citations
7.
Das, Shaon Kumar, Goutam Kumar Ghosh, R. K. Avasthe, & Kanchan Sinha. (2020). Compositional heterogeneity of different biochar: Effect of pyrolysis temperature and feedstocks. Journal of Environmental Management. 278(Pt 2). 111501–111501. 266 indexed citations breakdown →
8.
Sinha, Kanchan, et al.. (2018). Cointegration and Price Discovery Mechanism of Major Spices in India. 7(1). 18–24. 2 indexed citations
9.
Ray, Mrinmoy, et al.. (2018). Improved ARIMAX modal based on ANN and SVM approaches for forecasting rice yield using weather variables. The Indian Journal of Agricultural Sciences. 88(12). 1909–1913. 17 indexed citations
10.
Sinha, Kanchan, et al.. (2018). Hybrid linear time series approach for long term forecasting of crop yield. The Indian Journal of Agricultural Sciences. 88(8). 1275–1279. 10 indexed citations
11.
Sinha, Kanchan, et al.. (2018). Development of Hybrid Time Series Model using Machine Learning Techniques for Forecasting Crop Yield with Covariates. 1 indexed citations
12.
Lama, Achal, et al.. (2018). Modelling transmission of potato price volatility in West Bengal markets: MGARCH approach.. 3(1). 33–38. 1 indexed citations
13.
Kumar, Prakash, et al.. (2018). Role of Big Data in Agriculture-A Statistical Prospective. 1 indexed citations
14.
Paul, Ranjit Kumar, et al.. (2017). A hybrid wavelet based neural networks model for predicting monthly WPI of pulses in India. The Indian Journal of Agricultural Sciences. 87(6). 5 indexed citations
15.
Sinha, Kanchan, Bishal Gurung, Ranjit Kumar Paul, et al.. (2017). Volatility spillover using multivariate GARCH model: an application in futures and spot market price of black pepper.. 71(1). 21–28. 5 indexed citations
16.
Lama, Achal, Girish Kumar Jha, Bishal Gurung, Ranjit Kumar Paul, & Kanchan Sinha. (2016). VAR-MGARCH Models for Volatility Modelling of Pulses Prices: An Application. 3 indexed citations
17.
Paul, Ranjit Kumar & Kanchan Sinha. (2016). Forecasting crop yield: a comparative assessment of Arimax and Narx models.. 1(1). 77–85. 5 indexed citations
18.
Jha, Girish Kumar, et al.. (2013). Agricultural Price Forecasting Using Neural Network Model: An Innovative Information Delivery System. AgEcon Search (University of Minnesota, USA). 26(2). 229–239. 43 indexed citations
19.
Jha, Girish Kumar & Kanchan Sinha. (2012). Time-delay neural networks for time series prediction: an application to the monthly wholesale price of oilseeds in India. Neural Computing and Applications. 24(3-4). 563–571. 82 indexed citations
20.
Sinha, Kanchan. (2003). Citizenship degraded: Indian women in a modern state and a pre-modern society. Gender & Development. 11(3). 19–26. 7 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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