Hum Nath Bhandari

428 citations
10 papers · 256 · 1 hit paper · h-index 7

Impact in

Papers in

Hum Nath Bhandari

10 papers receiving 246 citations

Hum Nath Bhandari's Hit Papers

Predicting stock market index using LSTM 2022 · 169 citations
1690+1+2Years since publication50100150

Peers

Hum Nath Bhandari
Comparison fields: 5 of 64
  • Management Science and Operations Research 153
  • Finance 29
  • Economics and Econometrics 71
  • Signal Processing 21
  • Electrical and Electronic Engineering 79
Replace Sudeepa Roy Dey with:
Sudeepa Roy Dey India
Piotr Nowak Poland
Jin‐Lung Lin Taiwan
Alec N. Kercheval United States
Luca Grilli Italy
Yumo Xu United Kingdom
Xianhua Peng United States
Rolf Tschernig Germany
Blanka Horvath United Kingdom
Leonardo Rojas‐Nandayapa Australia
Hum Nath Bhandari relative to Sudeepa Roy Dey India Sudeepa Roy Dey's profile →
Citations per field
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Sudeepa Roy Dey · 1×
Citations per year

Countries citing papers authored by Hum Nath Bhandari

Since Specialization
Citations

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

Fields of papers citing papers by Hum Nath Bhandari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hum Nath Bhandari. 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 Hum Nath Bhandari. The network helps show where Hum Nath Bhandari may publish in the future.

Co-authors

The 10 scholars most cited alongside Hum Nath Bhandari, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hum Nath Bhandari Line = papers co-authored together Hum Nath Bhandari links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Predicting stock market index using LSTM
Hit paper breakdown →
2022169
2 202223
3 201719
4 202212
5 20199
6 20227
7 20186
8 20245
9 20245
10 20241

About Hum Nath Bhandari

Hum Nath Bhandari is a scholar working on Management Science and Operations Research, Economics and Econometrics, Atomic and Molecular Physics, and Optics, Signal Processing and Electrical and Electronic Engineering, having authored 10 papers that have together received 256 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (7 papers), Advanced Chemical Physics Studies (3 papers), Spectroscopy and Quantum Chemical Studies (2 papers), Energy Load and Power Forecasting (2 papers), Forecasting Techniques and Applications (2 papers), Time Series Analysis and Forecasting (2 papers), Market Dynamics and Volatility (2 papers) and Housing Market and Economics (1 paper). The work is most often cited by research in Management Science and Operations Research (153 citations), Finance (29 citations), Economics and Econometrics (71 citations), Signal Processing (21 citations) and Electrical and Electronic Engineering (79 citations). Hum Nath Bhandari has collaborated with scholars based in United States and India. Frequent co-authors include Nawa Raj Pokhrel, Ramchandra Rimal, Keshab Raj Dahal, William L. Hase, Subha Pratihar, Moumita Majumder, Amit Kumar Paul, Philip W. Smith, Keshab Dahal and Xinyou Ma. Their work appears in journals such as The Journal of Physical Chemistry C, Journal of Chemical Theory and Computation, Financial Innovation, The Journal of Physical Chemistry A and Annals of Data Science.

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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