On the public citation graph

Research on Market Stock Index Prediction Based on Network Security and Deep Learning

0 signed · 56 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Retraction Watch lists this work as retracted (export 2026-10-28; notice 2023-12-29, 10.1155/2023/9786431). OpenCitations Index CSV, figshare 24356626 v8 (2026-09-08) records 12 citing works; 5 have dates after the notice under the dataset’s date-resolution rule.

Dataset join, best-effort; this page does not check the publisher record. Retraction Watch data via Crossref Labs, used with credit; OpenCitations Index (CC0) and Meta (CC BY 4.0); dataset doi:10.7910/DVN/WT8VOA (CC BY 4.0).

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00382-017-3608-yopenalex-snapshot
On the skill of seasonal sea surface temperature forecasts in the California Current System and its connection to ENSO variability
inferredcites →https://doi.org/10.1007/s10489-016-0857-0openalex-snapshot
An efficient forecasting model based on an improved fuzzy time series and a modified group search optimizer
inferredcites →https://doi.org/10.1007/s11227-017-2228-yopenalex-snapshot
An innovative neural network approach for stock market prediction
inferredcites →https://doi.org/10.1007/s11276-018-1667-6openalex-snapshot
A deep learning method based on convolutional neural network for automatic modulation classification of wireless signals
inferredcites →https://doi.org/10.1016/j.chaos.2019.07.021openalex-snapshot
Research on application of fractional calculus in signal real-time analysis and processing in stock financial market
inferredcites →https://doi.org/10.1016/j.ins.2019.01.071openalex-snapshot
Fuzzy forecasting based on linear combinations of independent variables, subtractive clustering algorithm and artificial bee colony algorithm
inferredcites →https://doi.org/10.1016/j.ins.2020.09.031openalex-snapshot
Advantages of direct input-to-output connections in neural networks: The Elman network for stock index forecasting
inferredcites →https://doi.org/10.1016/j.knosys.2017.12.025openalex-snapshot
Improving stock market prediction via heterogeneous information fusion
inferredcites →https://doi.org/10.1016/j.scitotenv.2018.11.134openalex-snapshot
Interregional carbon compensation cost forecast and priority index calculation based on the theoretical carbon deficit: China as a case
inferredcites →https://doi.org/10.1016/j.scitotenv.2020.139404openalex-snapshot
Methodology for forecast and control of coastal harmful algal blooms by embedding a compound eutrophication index into the ecological risk index
inferredcites →https://doi.org/10.1016/j.solener.2019.06.041openalex-snapshot
Short-term solar power forecast with deep learning: Exploring optimal input and output configuration
inferredcites →https://doi.org/10.1017/jfm.2018.980openalex-snapshot
Deep learning of mixing by two ‘atoms’ of stratified turbulence
inferredcites →https://doi.org/10.1021/acs.jmedchem.8b00075openalex-snapshot
Intrinsic Property Forecast Index (iPFI) as a Rule of Thumb for Medicinal Chemists to Remove a Phototoxicity Liability
inferredcites →https://doi.org/10.1021/acsami.9b05857openalex-snapshot
Simultaneous Inverse Design of Materials and Structures via Deep Learning: Demonstration of Dipole Resonance Engineering Using Core–Shell Nanoparticles
inferredcites →https://doi.org/10.1038/nbt.4313openalex-snapshot
Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification
inferredcites →https://doi.org/10.1038/s41591-018-0320-3openalex-snapshot
A call for deep-learning healthcare
inferredcites →https://doi.org/10.1039/c9lc00721kopenalex-snapshot
Development and evaluation of inexpensive automated deep learning-based imaging systems for embryology
inferredcites →https://doi.org/10.1049/iet-ipr.2018.5727openalex-snapshot
Spatial‐spectral classification of hyperspectral images: a deep learning framework with Markov Random fields based modelling
inferredcites →https://doi.org/10.1057/jors.1975.90openalex-snapshot
A Forecast Monitoring and Revision System for Top Management
inferredcites →https://doi.org/10.1057/jors.2010.55openalex-snapshot
Estimating a retailer's base stock level: an optimal distribution center order forecast policy
inferredcites →https://doi.org/10.1091/mbc.e20-11-0689openalex-snapshot
Performance of deep learning restoration methods for the extraction of particle dynamics in noisy microscopy image sequences
inferredcites →https://doi.org/10.1093/mnras/stz010openalex-snapshot
Deep learning from 21-cm tomography of the Cosmic Dawn and Reionization
inferredcites →https://doi.org/10.1097/rli.0000000000000755openalex-snapshot
Deep Learning‐Based Automated Abdominal Organ Segmentation in the UK Biobank and German National Cohort Magnetic Resonance Imaging Studies
inferredcites →https://doi.org/10.1109/tbme.2019.2922235openalex-snapshot
A Deep Convolutional Neural Network Approach to Classify Normal and Abnormal Gastric Slow Wave Initiation From the High Resolution Electrogastrogram
inferredcites →https://doi.org/10.1109/tcyb.2014.2326888openalex-snapshot
Fuzzy Forecasting Based on Two-Factors Second-Order Fuzzy-Trend Logical Relationship Groups and the Probabilities of Trends of Fuzzy Logical Relationships
inferredcites →https://doi.org/10.1109/tec.2018.2873358openalex-snapshot
Deep Learning Based Module Defect Analysis for Large-Scale Photovoltaic Farms
inferredcites →https://doi.org/10.1109/tfuzz.2020.2966167openalex-snapshot
A Fuzzy Deep Neural Network with Sparse Autoencoder for Emotional Intention Understanding in Human-Robot Interaction
inferredcites →https://doi.org/10.1109/tmi.2019.2899328openalex-snapshot
Deep Learning for Fast and Spatially Constrained Tissue Quantification From Highly Accelerated Data in Magnetic Resonance Fingerprinting
inferredcites →https://doi.org/10.1109/tsm.2019.2958526openalex-snapshot
Simulation-Based Performance Assessment of Production Planning Models With Safety Stock and Forecast Evolution in Semiconductor Wafer Fabrication
inferredcites →https://doi.org/10.1109/twc.2020.2968430openalex-snapshot
Convolutional Neural Network-Based Multiple-Rate Compressive Sensing for Massive MIMO CSI Feedback: Design, Simulation, and Analysis
inferredcites →https://doi.org/10.1136/heartjnl-2019-316496openalex-snapshot
Deep learning in congenital heart disease imaging: hope but not haste
inferredcites →https://doi.org/10.1161/strokeaha.120.032604openalex-snapshot
Letter by Amukotuwa and Dehkharghani Regarding Article, “Deep Learning Based Software to Identify Large Vessel Occlusion on Noncontrast Computed Tomography”
inferredcites →https://doi.org/10.1364/oe.27.036002openalex-snapshot
Photonic human identification based on deep learning of back scattered laser speckle patterns
inferredcites →https://doi.org/10.2112/si94-077.1openalex-snapshot
Design of Container Terminal Handling System Based on Index Forecast and Economic Evaluation
inferredcites →https://doi.org/10.2320/jinstmet.j2017034openalex-snapshot
Dynamic Material Flow Analysis of Copper and Copper Alloy in Global Scale —Forecast of In-Use Stock and Inputs and the Estimation of Scrap Recovery Potential—

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4201423openalex-extracted
Stock Market Prediction Using Natural Language Processing - A Survey
inferred← citeshttps://doi.org/10.1007/978-3-031-36402-0_23openalex-snapshot
Evaluating the Performance of Diverse Machine Learning Approaches in Stock Market Forecasting
inferred← citeshttps://doi.org/10.1007/978-981-99-6547-2_12openalex-snapshot
Comparative Study of CNN and LSTM on Short-Term Future Stock Price Prediction
inferred← citeshttps://doi.org/10.1016/j.bir.2023.10.005openalex-snapshot
Price prediction of the Borsa Istanbul banks index with traditional methods and artificial neural networks
inferred← citeshttps://doi.org/10.1051/itmconf/20224403060openalex-snapshot
Stock Price Prediction using Facebook Prophet
inferred← citeshttps://doi.org/10.1063/5.0254170openalex-snapshot
Candlestick pattern analysis for stock prediction
inferred← citeshttps://doi.org/10.1109/icbds58040.2023.10346583openalex-snapshot
Cryptocurrency Prediction and Analysis between Supervised and Unsupervised Learning with XAI
inferred← citeshttps://doi.org/10.1109/icrito56286.2022.9964748openalex-snapshot
Simulating Optimized Stock Price Prediction Using Deep Learning Mechanism
inferred← citeshttps://doi.org/10.1109/icscan58655.2023.10395609openalex-snapshot
Predicting the Price of Stock Using Deep Learning Algorithms
inferred← citeshttps://doi.org/10.1155/2023/9786431openalex-snapshot
Retracted: Research on Market Stock Index Prediction Based on Network Security and Deep Learning
inferred← citeshttps://doi.org/10.17533/udea.mut.1949openalex-snapshot
El food design como instrumento para el desarrollo de estrategias de co-creación comunitaria y el fortalecimiento del turismo regenerativo y la gastronomía sostenible. Caso de estudio: Sector La Mariposa, Usaquén.
inferred← citeshttps://doi.org/10.21015/vtse.v12i4.1949openalex-snapshot
Stock Market Prediction using LSTM Model on the News and Social Media Data
inferred← citeshttps://doi.org/10.21123/bsj.2024.10017openalex-snapshot
An Analytical Comparison of the Behavior of Machine Learning and Deep Learning in Stock Market Prediction
inferred← citeshttps://doi.org/10.2139/ssrn.4842130openalex-snapshot
An Examination of the Market Performance of Malawi Stock Exchange
inferred← citeshttps://doi.org/10.2139/ssrn.4887716openalex-snapshot
An Examination of the Market Performance of Malawi Stock Exchange
inferred← citeshttps://doi.org/10.2174/1872212118666230303154251openalex-snapshot
An Analytic Review on Stock Market Price Prediction using Machine Learning and Deep Learning Techniques
inferred← citeshttps://doi.org/10.35193/bseufbd.1087654openalex-snapshot
Finansal Zaman Serilerini Tahminlemede Kullanılan Yöntemlere Genel Bir Bakış
inferred← citeshttps://doi.org/10.5121/csit.2022.1214openalex-snapshot
Computer Science and Information Technology Trends
inferred← citeshttps://doi.org/10.5121/csit.2022.121404openalex-snapshot
Stock Market Prediction using Natural Language Processing -a Survey
inferred← citeshttps://doi.org/10.55041/ijsrem49113openalex-snapshot
Stock Price Prediction Using Machine Learning
inferred← citeshttps://doi.org/10.55188/ijifsd.v17i3.1112openalex-snapshot
Modelling and Forecasting Sharīʿah-Compliant Stocks
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.