State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability

Lecture notes in networks and systems, Journal Year: 2020, Volume and Issue: unknown, P. 228 - 238

Published: Jan. 1, 2020

Language: Английский

---

Deep Learning and Machine Learning in Hydrological Processes, Climate Change and Earth Systems: A Systematic Review

Published: Aug. 15, 2019

Artificial intelligence methods and application have recently shown great contribution in modeling prediction of the hydrological processes, climate change, earth systems. Among them, deep learning machine mainly reported being essential for achieving higher accuracy, robustness, efficiency, computation cost, overall model performance. This paper presents state art applications this realm current state, future trends are discussed. The survey advances presented through a novel classification methods. concludes that is still first stages development, research progressing. On other hand, already established fields, with performance emerging ensemble techniques hybridization.

Language: Английский

---

State of the Art Survey of Deep Learning and Machine Learning Models for Smart Cities and Urban Sustainability

Published: Oct. 8, 2020

Deep learning (DL) and machine (ML) methods have recently contributed to the advancement of models in various aspects prediction, planning, uncertainty analysis smart cities urban development. This paper presents state art DL ML used this realm. Through a novel taxonomy, advances model development new application domains sustainability are presented. Findings reveal that five been most applied address different cities. These artificial neural networks; support vector machines; decision trees; ensembles, Bayesians, hybrids, neuro-fuzzy; deep learning. It is also disclosed energy, health, transport main their problems.

Language: Английский

---

COVID-19 Outbreak Prediction with Machine Learning

Published: Oct. 6, 2020

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among standard global pandemic prediction, simple epidemiological statistical have received more attention authorities, they popular in media. Due a high level of uncertainty lack essential data, shown low accuracy long-term prediction. Although literature includes several attempts address this issue, generalization robustness abilities existing needs be improved. This paper presents comparative analysis machine learning soft computing predict as an alternative SIR SEIR models. wide range investigated, two showed promising results (i.e., multi-layered perceptron, MLP, adaptive network-based fuzzy inference system, ANFIS). Based on reported here, due highly complex nature variation its behavior from nation-to-nation, study suggests effective tool model outbreak. provides initial benchmarking demonstrate potential future research. Paper further that real novelty can realized through integrating

Language: Английский

---

List of Deep Learning Models

Published: Aug. 13, 2019

Deep learning (DL) algorithms have recently emerged from machine and soft computing techniques. Since then, several deep been introduced to scientific communities are applied in various application domains. Today the usage of DL has become essential due their intelligence, efficient learning, accuracy robustness model building. However, literature, a comprehensive list not yet. This paper provides most popular algorithms, along with applications

Language: Английский

---