Advanced Machine Learning Applications in Big Data Analytics

• Diğer Yazarlar: Li, Taiyong (Editör), Deng, Wu (Editör), Wu, Jiang (Editör)
• Materyal Türü: Elektronik Kitap Bölümü
• Dil: İngilizce
• Baskı/Yayın Bilgisi: MDPI - Multidisciplinary Digital Publishing Institute 2023
• Konular: Technology: general issues; History of engineering & technology; energy storage; model predictive control; peak shaving and frequency regulation; output optimization; global optimization; meta-heuristic; support vector machine swarm intelligence; hyperspectral image classification; CNN; ELM; PSO; deep feature; butterfly optimization algorithm; random replacement; crisscross search; overseas Chinese associations; support vector machine; short-term traffic-flow forecasting; bagging model; stacking model; ridge regression; error coefficient; least squares method; support vector machines; principal component analysis; quick access recorder; mean absolute error; high-plateau flight; event extraction; event type; event trigger words; stock announcement news; stock return; traffic flow forecasting; long short-term memory network; graph convolutional network; target detection; infrared; deep learning; YOLOv5 algorithm; design science research; performance analysis; machine learning; classification algorithms; clustering algorithms; pilot abnormal behavior; behavior detection; YOLOv4 algorithm; CBAM; flight safety; fault diagnosis; variational mode decomposition; composite multi-scale dispersion entropy; particle swarm optimization; deep belief network; CBCFI; combined prediction model; ARMA; GM; GA; BP; hierarchical clustering; Jaccard distance; membership grade; community clustering; lightweight neural networks; attentional mechanisms; Hemerocallis citrina Baroni; maturity detection; cloud; digital archives; confidentiality management; information system; emotion-cause pair extraction; heterogeneous graph; graph attention network; hierarchical model; spatial-temporal systems; neural networks; information systems; forecasting; time series; coupled map lattice; polymorphic mapping; color image; hash function; pixel level; differential evolution; capacitated vehicle routing planning; saving mileage; gravity search; object detection; computer vision; border patrol; COVID-19; warning system; PROPHET; health; quantum dynamics; neural architecture search; image classification; swarm intelligence; whale optimization algorithm; extreme learning machine; talent stability prediction; adversarial attacks; document classification; NLP; convolutional neural networks; disease classification; generative adversarial network; tomato leaf; multi-strategy; dual-update strategy; mean-semivariance model; portfolio optimization; DNA computing; DNA sequences design; improved matrix particle swarm optimization algorithm (IMPSO); opposition-based learning; signal-to-noise ratio distance; time series classification; complementary ensemble empirical mode decomposition (CEEMD); MultiRocket; feature selection; hybrid model; multi-behavior recommendation; sequential recommendation; graph neural network; embedding propagation; 1D quadratic chaotic system; image encryption; splicing model; DNA coding; BaaS system; blockchain consensus algorithm; KNN; service level agreement; transaction priority; data stream mining; forex; online learning; adaptive learning; incremental learning; sliding window; concept drift; financial time series forecasting; n/a
• Online Erişim: DOAB: download the publication; DOAB: description of the publication

With the development of computer technology and communication technology, various industries have collected a large amount of data in different forms, so-called big data. How to obtain valuable knowledge from these data is a very challenging task. Machine learning is such a direct and effective meth...