Musa Mammadov

1.3k total citations
77 papers, 909 citations indexed

About

Musa Mammadov is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Management Science and Operations Research. According to data from OpenAlex, Musa Mammadov has authored 77 papers receiving a total of 909 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 25 papers in Computational Theory and Mathematics and 17 papers in Management Science and Operations Research. Recurrent topics in Musa Mammadov's work include Bayesian Modeling and Causal Inference (13 papers), Optimization and Variational Analysis (12 papers) and Advanced Optimization Algorithms Research (10 papers). Musa Mammadov is often cited by papers focused on Bayesian Modeling and Causal Inference (13 papers), Optimization and Variational Analysis (12 papers) and Advanced Optimization Algorithms Research (10 papers). Musa Mammadov collaborates with scholars based in Australia, China and Sri Lanka. Musa Mammadov's co-authors include Sona Taheri, John Yearwood, Ibrahim A. Sultan, Sattar Seifollahi, Refail Kasımbeyli, A. Golbabai, Limin Wang, Salih Aytar, Serpil Pehli̇van and Lei Zhao and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and European Journal of Operational Research.

In The Last Decade

Musa Mammadov

69 papers receiving 851 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Musa Mammadov Australia	18	263	176	141	125	115	77	909
Julio López Chile	17	708 2.7×	89 0.5×	47 0.3×	40 0.3×	73 0.6×	54	1.2k
C. J. Price New Zealand	13	208 0.8×	289 1.6×	325 2.3×	38 0.3×	46 0.4×	54	719
Abdel-Rahman Hedar Egypt	15	751 2.9×	566 3.2×	170 1.2×	27 0.2×	74 0.6×	67	1.2k
Zhong Wang China	15	89 0.3×	99 0.6×	44 0.3×	53 0.4×	121 1.1×	60	782
Alireza Nazemi Iran	22	508 1.9×	218 1.2×	365 2.6×	72 0.6×	150 1.3×	108	1.4k
Lingfeng Niu China	16	711 2.7×	69 0.4×	31 0.2×	27 0.2×	54 0.5×	82	1.2k
Yi Zhou China	15	570 2.2×	56 0.3×	62 0.4×	44 0.4×	116 1.0×	99	1.3k
K. Spingarn United States	11	200 0.8×	93 0.5×	48 0.3×	59 0.5×	270 2.3×	43	763
Erwie Zahara Taiwan	10	972 3.7×	527 3.0×	83 0.6×	98 0.8×	72 0.6×	16	1.7k
K. M. Ragsdell United States	16	390 1.5×	431 2.4×	95 0.7×	161 1.3×	183 1.6×	52	1.1k

Countries citing papers authored by Musa Mammadov

Since Specialization

Citations

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

Fields of papers citing papers by Musa Mammadov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Musa Mammadov

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

All Works

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20 of 20 papers shown

Mammadov, Musa, et al.. (2024). A Novel Hybrid Spatiotemporal Missing Value Imputation Approach for Rainfall Data: An Application to the Ratnapura Area, Sri Lanka. Applied Sciences. 14(3). 999–999. 4 indexed citations

Mammadov, Musa, et al.. (2024). Granger Causality-Based Forecasting Model for Rainfall at Ratnapura Area, Sri Lanka: A Deep Learning Approach. SHILAP Revista de lepidopterología. 6(4). 1124–1151. 3 indexed citations

Mammadov, Musa, et al.. (2023). An Application of Ensemble Spatiotemporal Data Mining Techniques for Rainfall Forecasting. SHILAP Revista de lepidopterología. 6–6. 1 indexed citations

Wang, Limin, et al.. (2020). Model Weighting for One-Dependence Estimators by Measuring the Independence Assumptions. IEEE Access. 8. 150465–150477. 1 indexed citations

Mammadov, Musa, et al.. (2020). FULL-TEXT RESOURCES OF THE PROJECT TYPE CREATED IN THE PRESIDENTIAL LIBRARY OF THE OFFICE OF THE PRESIDENT OF THE REPUBLIC OF AZERBAIJAN AS AN INNOVATIVE RESOURCE TYPE OF ELECTRONIC LIBRARY. SHILAP Revista de lepidopterología. 4(9).

Mammadov, Musa, et al.. (2019). An Improved Probabilistic Neural Network Model for Directional Prediction of a Stock Market Index. Applied Sciences. 9(24). 5334–5334. 12 indexed citations

Wang, Limin, et al.. (2018). RDE: A novel approach to improve the classification performance and expressivity of KDB. PLoS ONE. 13(7). e0199822–e0199822. 2 indexed citations

Mammadov, Musa, et al.. (2017). Optimality conditions via weak subdifferentials in reflexive Banach spaces. DergiPark (Istanbul University). 1 indexed citations

Mammadov, Musa, et al.. (2017). Convergence of trajectories in infinite horizon optimization. International journal of nonlinear analysis and applications. 8(1). 123–131.

10.

Mammadov, Musa, et al.. (2016). Return Distributions of Selected Financial Indices that Associated with Stock Indices. 6(3). 156–162.

11.

Mammadov, Musa, et al.. (2015). Identifying Distributions of Selected Stock Returns. 16(2). 7–22. 2 indexed citations

12.

Mammadov, Musa, et al.. (2014). Sigma supporting cone and optimality conditions in non-convex problems. Far East Journal of Mathematical Sciences (FJMS). 91(2). 169–190.

13.

Bagirov, Adil, et al.. (2012). Application of Optimisation-Based Data Mining Techniques to Medical Data Sets: A Comparative Analysis. FedUni ResearchOnline (Federation University Australia). 41–46. 1 indexed citations

14.

Taheri, Sona, Musa Mammadov, & Adil Bagirov. (2011). Improving naive Bayes classifier using conditional probabilities. FedUni ResearchOnline (Federation University Australia). 63–68. 18 indexed citations

15.

Ivanov, Anatoli F. & Musa Mammadov. (2010). GLOBAL STABILITY, PERIODIC SOLUTIONS, AND OPTIMAL CONTROL IN A NONLINEAR DIFFERENTIAL DELAY MODEL. Electronic Journal of Differential Equations. 2010(19). 177–188. 3 indexed citations

16.

Mammadov, Musa, et al.. (2008). A NEW STRATEGY FOR TRAINING RBF NETWORK WITH APPLICATIONS TO NONLINEAR INTEGRAL EQUATIONS. 19(25). 1–7. 1 indexed citations

17.

Mammadov, Musa, et al.. (2008). A filled function method for constrained nonlinear equations. FedUni ResearchOnline (Federation University Australia). 4(1). 9–18. 3 indexed citations

18.

Mammadov, Musa, et al.. (2007). Effectiveness of using quantified intermarket influence for predicting trading signals of stock markets. FedUni ResearchOnline (Federation University Australia). 70. 167–175. 8 indexed citations

19.

Mammadov, Musa, A. M. Rubinov, & John Yearwood. (2006). The study of drug–reaction relationships using global optimization techniques. Optimization methods & software. 22(1). 99–126. 13 indexed citations

20.

Mammadov, Musa, et al.. (2006). Coverage in WLAN: Optimization Model and Algorithm. UTS ePRESS (University of Technology Sydney). 302–307. 5 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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