The Random Hivemind: An Ensemble Deep Learner Application to Solar Energetic Particle Prediction Problem

Autor: O'Keefe, Patrick M., Sadykov, Viacheslav, Kosovichev, Alexander, Kitiashvili, Irina N., Oria, Vincent, Nita, Gelu M., Francis, Fraila, Chong, Chun-Jie, Kosovich, Paul, Ali, Aatiya, Marroquin, Russell D.

The application of machine learning and deep learning, including the wide use of non-ensemble, conventional neural networks (CoNN), for predicting various phenomena has become very popular in recent years thanks to the efficiencies and the abilities

Externí odkaz: http://arxiv.org/abs/2303.08092

Predicting Solar Proton Events of Solar Cycles 22-24 using GOES Proton & soft X-Ray flux features

Autor: Ali, Aatiya, Sadykov, Viacheslav, Kosovichev, Alexander, Kitiashvili, Irina N., Oria, Vincent, Nita, Gelu M., Illarionov, Egor, O'Keefe, Patrick M., Francis, Fraila, Chong, Chun-Jie, Kosovich, Paul, Marroquin, Russell D.

Solar Energetic Particle (SEP) events and their major subclass, Solar Proton Events (SPEs), can have unfavorable consequences on numerous aspects of life and technology, making them one of the most harmful effects of solar activity. Garnering knowled

Externí odkaz: http://arxiv.org/abs/2303.05446

Review of Solar Energetic Particle Prediction Models

Autor: Whitman, Kathryn, Egeland, Ricky, Richardson, Ian G., Allison, Clayton, Quinn, Philip, Barzilla, Janet, Kitiashvili, Irina, Sadykov, Viacheslav, Bain, Hazel M., Dierckxsens, Mark, Mays, M. Leila, Tadesse, Tilaye, Lee, Kerry T., Semones, Edward, Luhmann, Janet G., Núñez, Marlon, White, Stephen M., Kahler, Stephen W., Ling, Alan G., Smart, Don F., Shea, Margaret A., Tenishev, Valeriy, Boubrahimi, Soukaina F., Aydin, Berkay, Martens, Petrus, Angryk, Rafal, Marsh, Michael S., Dalla, Silvia, Crosby, Norma, Schwadron, Nathan A., Kozarev, Kamen, Gorby, Matthew, Young, Matthew A., Laurenza, Monica, Cliver, Edward W., Alberti, Tommaso, Stumpo, Mirko, Benella, Simone, Papaioannou, Athanasios, Anastasiadis, Anastasios, Sandberg, Ingmar, Georgoulis, Manolis K., Ji, Anli, Kempton, Dustin, Pandey, Chetraj, Li, Gang, Hu, Junxiang, Zank, Gary P., Lavasa, Eleni, Giannopoulos, Giorgos, Falconer, David, Kadadi, Yash, Fernandes, Ian, Dayeh, Maher A., Muñoz-Jaramillo, Andrés, Chatterjee, Subhamoy, Moreland, Kimberly D., Sokolov, Igor V., Roussev, Ilia I., Taktakishvili, Aleksandre, Effenberger, Frederic, Gombosi, Tamas, Huang, Zhenguang, Zhao, Lulu, Wijsen, Nicolas, Aran, Angels, Poedts, Stefaan, Kouloumvakos, Athanasios, Paassilta, Miikka, Vainio, Rami, Belov, Anatoly, Eroshenko, Eugenia A., Abunina, Maria A., Abunin, Artem A., Balch, Christopher C., Malandraki, Olga, Karavolos, Michalis, Heber, Bernd, Labrenz, Johannes, Kühl, Patrick, Kosovichev, Alexander G., Oria, Vincent, Nita, Gelu M., Illarionov, Egor, O’Keefe, Patrick M., Jiang, Yucheng, Fereira, Sheldon H., Ali, Aatiya, Paouris, Evangelos, Aminalragia-Giamini, Sigiava, Jiggens, Piers, Jin, Meng, Lee, Christina O., Palmerio, Erika, Bruno, Alessandro, Kasapis, Spiridon, Wang, Xiantong, Chen, Yang, Sanahuja, Blai, Lario, David, Jacobs, Carla, Strauss, Du Toit, Steyn, Ruhann, van den Berg, Jabus, Swalwell, Bill, Waterfall, Charlotte, Nedal, Mohamed, Miteva, Rositsa, Dechev, Momchil, Zucca, Pietro, Engell, Alec, Maze, Brianna, Farmer, Harold, Kerber, Thuha, Barnett, Ben, Loomis, Jeremy, Grey, Nathan, Thompson, Barbara J., Linker, Jon A., Caplan, Ronald M., Downs, Cooper, Török, Tibor, Lionello, Roberto, Titov, Viacheslav, Zhang, Ming, Hosseinzadeh, Pouya

Publikováno v: In Advances in Space Research 15 December 2023 72(12):5161-5242

The Random Hivemind: An Ensemble Deep Learner. A Case Study of Application to Solar Energetic Particle Prediction Problem

Autor: O'Keefe, Patrick M., Sadykov, Viacheslav, Kosovichev, Alexander, Kitiashvili, Irina N., Oria, Vincent, Nita, Gelu M., Francis, Fraila, Chong, Chun-Jie, Kosovich, Paul, Ali, Aatiya, Marroquin, Russell D.

Deep learning has become a popular trend in recent years in the machine learning community and has even occasionally become synonymous with machine learning itself thanks to its efficiency, malleability, and ability to operate free of human intervent

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::96e80576ebbd0d3ec1f9b43edf6744a2
http://arxiv.org/abs/2303.08092

PONZI SCHEMES IN BANKRPUTCY.

Autor: O'Keefe, Patrick M., Long, Russell D., McElwee, Michael S.

Publikováno v: Debt Cubed. Nov/Dec2007, Vol. 22 Issue 6, p6-11. 6p.