المؤلفون: P. Sathishkumar, A. Gnanabaskaran, M. Saradha, R. Gopinath

المصدر: Ain Shams Engineering Journal, Vol 15, Iss 12, Pp 103052- (2024)

مصطلحات موضوعية: Wireless sensor network (WSN), Denial of service (DoS), Intrusion detection system (IDS), Crow search algorithm, Deep LSTM algorithm, Engineering (General). Civil engineering (General), TA1-2040

وصف الملف: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2090447924004271; https://doaj.org/toc/2090-4479

URL الوصول: https://doaj.org/article/3a9bc6f4d4a94c8b9d73640762d5720f

المؤلفون: Ganji Tejasree, L. Agilandeeswari

المصدر: Egyptian Journal of Remote Sensing and Space Sciences, Vol 27, Iss 1, Pp 52-68 (2024)

مصطلحات موضوعية: Land use/land cover (LULC), Deep-LSTM, Auto-encoder, Ranking based method, Feature extraction, Band selection, Geodesy, QB275-343

وصف الملف: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1110982324000048; https://doaj.org/toc/1110-9823

URL الوصول: https://doaj.org/article/4df5cac479764f2793e8f2146f11fc3e

المؤلفون: Azhar Ahmed Bilal, O. Ayhan Erdem, Sinan Toklu

المصدر: IEEE Access, Vol 12, Pp 70089-70104 (2024)

مصطلحات موضوعية: Long short term memory (deep LSTM), natural language processing (NLP), principal component analysis (PCA), sentiment analysis (SA), singular value decomposition (SVD), Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/10530269/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/a5388fd63b7c486bb4b9c2adc2711cab

المؤلفون: Dandi Mochamad Reza, Satria Mandala, Salim M. Zaki, Eileen Su Lee Ming

المصدر: Jurnal Nasional Teknik Elektro, Pp 82-88 (2023)

مصطلحات موضوعية: arrhythmia, electrocardiogram, deep learning, autoencoder, deep lstm autoencoder, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://jnte.ft.unand.ac.id/index.php/jnte/article/view/1117; https://doaj.org/toc/2302-2949; https://doaj.org/toc/2407-7267

URL الوصول: https://doaj.org/article/dd399102940b4f358797433e7ba335d4

المؤلفون: Misbah Iqbal, Carman K. M. Lee, Kin Lok Keung, Zhonghao Zhao

المصدر: Mathematics, Vol 12, Iss 23, p 3698 (2024)

مصطلحات موضوعية: fault diagnosis, transfer learning, fine-tuning, deep LSTM, empirical mode decomposition, Mathematics, QA1-939

وصف الملف: electronic resource

Relation: https://www.mdpi.com/2227-7390/12/23/3698; https://doaj.org/toc/2227-7390

URL الوصول: https://doaj.org/article/79d47c5e42034a4bad87c6532b6a2220

المؤلفون: Shang kui Yang, Won jun Chung, Fan Yang

المصدر: Heliyon, Vol 10, Iss 10, Pp e31408- (2024)

مصطلحات موضوعية: Image emotion perception computing, Deep LSTM model, Dynamic Multi-Task Hyper Graphs Learning, Packaging design evaluation, Science (General), Q1-390, Social sciences (General), H1-99

وصف الملف: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2405844024074395; https://doaj.org/toc/2405-8440

URL الوصول: https://doaj.org/article/f17ab5b570b44c80b4482df4bcdafeb7

المؤلفون: Amirhossein Samii, Hojat Karami, Hamidreza Ghazvinian, Amirsaeed Safari, Yashar Dadrasajirlou

المصدر: Journal of Soft Computing in Civil Engineering, Vol 7, Iss 2, Pp 155-175 (2023)

مصطلحات موضوعية: evaporation pan, deep-lstm, mlp, meteorological data, semnan, garmsar, Technology

وصف الملف: electronic resource

Relation: https://www.jsoftcivil.com/article_168924_e72329148fe08c78d8b5c0b703ea3227.pdf; https://doaj.org/toc/2588-2872

URL الوصول: https://doaj.org/article/9dfe9e7de4854451bec0bd794edbc20e

المؤلفون: Snehal Rathi, Kamal Kant Hiran, Sachin Sakhare

المصدر: Array, Vol 19, Iss , Pp 100315- (2023)

مصطلحات موضوعية: E-learning, Higher education, Affective states, Deep LSTM, Squirrel search algorithm, Rider optimization algorithm, Computer engineering. Computer hardware, TK7885-7895, Electronic computers. Computer science, QA75.5-76.95

وصف الملف: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2590005623000401; https://doaj.org/toc/2590-0056

URL الوصول: https://doaj.org/article/0abe1b73f17944ad8d80d706747c6335

المؤلفون: R. Aiyshwariya Devi, A.R. Arunachalam

المصدر: High-Confidence Computing, Vol 3, Iss 2, Pp 100117- (2023)

مصطلحات موضوعية: Deep LSTM, Improved Elliptic Curve Cryptography, Malware detection, Prediction of different kinds of attacks, IoT gadgets, Electronic computers. Computer science, QA75.5-76.95

وصف الملف: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2667295223000156; https://doaj.org/toc/2667-2952

URL الوصول: https://doaj.org/article/bcccf2a8f8294814b0d4d97f0189dec3

المؤلفون: R. Trabelsi, R. Khemmar, B. Decoux, J.-Y. Ertaud, R. Boutteau

المصدر: IEEE Access, Vol 10, Pp 55794-55804 (2022)

مصطلحات موضوعية: Deep LSTM, attention mechanism, STAF, road scenes, behaviors understanding, smart mobility, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/9779713/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/e3ba7d66532b47e594283b40be1bc679

المؤلفون: Bassant M. Elbagoury, Luige Vladareanu, Victor Vlădăreanu, Abdel Badeeh Salem, Ana-Maria Travediu, Mohamed Ismail Roushdy

المصدر: Sensors; Volume 23; Issue 7; Pages: 3500

مصطلحات موضوعية: artificial intelligence, mobile health, stroke monitoring, iomt-stacked convolutional neural networks, GMDH neural networks, Deep LSTM, biomedical EMG signal processing

وصف الملف: application/pdf

Relation: Sensors and Robotics; https://dx.doi.org/10.3390/s23073500

الاتاحة: https://doi.org/10.3390/s23073500

المؤلفون: Belhassen Akrout, Sana Fakhfakh

المصدر: Electronics; Volume 12; Issue 4; Pages: 965

مصطلحات موضوعية: multilevel driver fatigue detection, deep LSTM network, MobileNetV3 transfer learning, features extraction, Google mediapipe face mesh

وصف الملف: application/pdf

Relation: https://dx.doi.org/10.3390/electronics12040965

الاتاحة: https://doi.org/10.3390/electronics12040965

المؤلفون: Jiyu Chen, Mingming Gao

المصدر: IEEE Access, Vol 9, Pp 147328-147342 (2021)

مصطلحات موضوعية: SO₂ prediction, improved mean impact value method, wide and deep LSTM, deep learning, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/9591619/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/b56297d45b334998bd7b44510545b6e6

المؤلفون: Fatih Demir, Abdulkadir Sengur, Ali Ari, Kamran Siddique, Mohammed Alswaitti

المصدر: IEEE Access, Vol 9, Pp 149456-149464 (2021)

مصطلحات موضوعية: Convolutional structure, deep LSTM network, feature mapping, PD diagnosis, speech disorders, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

وصف الملف: electronic resource

Relation: https://ieeexplore.ieee.org/document/9598908/; https://doaj.org/toc/2169-3536

URL الوصول: https://doaj.org/article/480129834d834f12bb790643444cb80e

المؤلفون: Elif Ecem Bas, Mohamed A. Moustafa

المصدر: Machine Learning and Knowledge Extraction, Vol 2, Iss 4, Pp 469-489 (2020)

مصطلحات موضوعية: real-time hybrid simulation (RTHS), machine learning, deep learning, deep long short-term memory (Deep-LSTM) networks, metamodel, seismic response, Computer engineering. Computer hardware, TK7885-7895

وصف الملف: electronic resource

Relation: https://www.mdpi.com/2504-4990/2/4/26; https://doaj.org/toc/2504-4990

URL الوصول: https://doaj.org/article/72c022f4b5ef4862ae4b86e3cb21e14f

المؤلفون: Bing Liu, Jichong Lei, Jinsen Xie, Jianliang Zhou

المصدر: Energies; Volume 15; Issue 22; Pages: 8629

مصطلحات موضوعية: nuclear power plant, PCTRAN, deep learning, fault diagnosis, deep LSTM

وصف الملف: application/pdf

Relation: A: Sustainable Energy; https://dx.doi.org/10.3390/en15228629

الاتاحة: https://doi.org/10.3390/en15228629

المؤلفون: Andrey Gorshenin, Victor Kuzmin

المصدر: Mathematics; Volume 10; Issue 4; Pages: 589

مصطلحات موضوعية: feature selection, finite normal mixtures, moving separation of mixtures, deep LSTM, neural network architectures, deep learning, turbulent plasma, air–sea fluxes

وصف الملف: application/pdf

Relation: Mathematics and Computer Science; https://dx.doi.org/10.3390/math10040589

الاتاحة: https://doi.org/10.3390/math10040589

المؤلفون: Rajasekaran Rajamoorthy, Hemachandira V. Saraswathi, Jayanthi Devaraj, Padmanathan Kasinathan, Rajvikram Madurai Elavarasan, Gokulalakshmi Arunachalam, Tarek M. Mostafa, Lucian Mihet-Popa

المصدر: Sustainability; Volume 14; Issue 3; Pages: 1355

مصطلحات موضوعية: energy forecasting, deep long short-term memory (deep LSTM), Sailfish Optimizer (SO), Whale Optimization Algorithm (WOA)

جغرافية الموضوع: agris

وصف الملف: application/pdf

Relation: https://dx.doi.org/10.3390/su14031355

الاتاحة: https://doi.org/10.3390/su14031355

المؤلفون: F. Rundo, R. Leotta, F. Trenta, G. Bellitto, F. Proietto Salanitri, V. Piuri, A. Genovese, R. Donida Labati, F. Scotti, C. Spampinato, S. Battiato

المساهمون: F. Imai, C. Distante, S. Battiato, F. Rundo, R. Leotta, F. Trenta, G. Bellitto, F. Proietto Salanitri, V. Piuri, A. Genovese, R. Donida Labati, F. Scotti, C. Spampinato

مصطلحات موضوعية: Drowsine, Deep learning, D-CNN, Deep-LSTM, PPG (PhotoPlethysmoGraphy), Settore INF/01 - Informatica, Settore ING-INF/05 - Sistemi di Elaborazione delle Informazioni

Relation: info:eu-repo/semantics/altIdentifier/isbn/9789897585111; info:eu-repo/semantics/altIdentifier/wos/WOS:000821069200008; ispartofbook:Proceedings of the International Conference on Image Processing and Vision Engineering. Volume 1; IMPROVE : April, 28 - 30; firstpage:81; lastpage:90; numberofpages:10; alleditors:F. Imai, C. Distante, S. Battiato; https://hdl.handle.net/2434/812608; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85125199858

الاتاحة: https://hdl.handle.net/2434/812608
https://doi.org/10.5220/0010381000810090

المؤلفون: Abdel-Nasser, Mohamed, Mahmoud, Karar, Lehtonen, Matti

المساهمون: Department of Electrical Engineering and Automation, Power Systems and High Voltage Engineering, Universidad Rovira i Virgili, Aalto-yliopisto, Aalto University

مصطلحات موضوعية: Photovoltaic, Irradiance forecasting, Deep LSTM, Choquet integral

وصف الملف: 1873-1881; application/pdf

Relation: IEEE Transactions on Industrial Informatics; Volume 17, issue 3; Abdel-Nasser, M, Mahmoud, K & Lehtonen, M 2021, ' Reliable Solar Irradiance Forecasting Approach Based on Choquet Integral and Deep LSTMs ', IEEE Transactions on Industrial Informatics, vol. 17, no. 3, 9097938, pp. 1873-1881 . https://doi.org/10.1109/TII.2020.2996235; PURE UUID: 3fb762eb-9179-4ad5-8323-cbd9ffb155ae; PURE ITEMURL: https://research.aalto.fi/en/publications/3fb762eb-9179-4ad5-8323-cbd9ffb155ae; PURE LINK: http://www.scopus.com/inward/record.url?scp=85097720384&partnerID=8YFLogxK; PURE FILEURL: https://research.aalto.fi/files/56836995/ELEC_Abdel_Nasser_Reliable_Solar_Irradiance_IEEETraIndInf_2020_authoracceptedmanuscript.pdf; https://aaltodoc.aalto.fi/handle/123456789/103185; URN:NBN:fi:aalto-202103222463

الاتاحة: https://aaltodoc.aalto.fi/handle/123456789/103185
https://doi.org/10.1109/TII.2020.2996235