5/10/2023 0 Comments Ipulse tens manual![]() Furthermore, different classifiers are used for baseline experiment and the model is evaluated on various word embedding vector methods. In the LSTM-Boost model, the dataset is divided into three categories, and PCA and LSTM networks are applied to each part of the dataset to obtain the most significant variance and reduce the weighted error of the weak hypothesis of the model. The proposed LSTM-BOOST model uses the modified AdaBoost algorithm employing principal component analysis(PCA) along with LSTM networks. This paper proposes an offensive text classification algorithm named LSTM-BOOST employing Long Short-Term Memory(LSTM) model with ensemble learning to recognize offensive Bengali texts in various social media platforms. Recently, offensive content has become increasingly popular for harassing and criticizing people on numerous social media platforms. According to the analysis, AI algorithms such as ANN, RNN/LSTM, CNN/R-CNN, DNN, and SVM/LS-SVM have a higher impact on the various smart city domains. Since the epidemic hit cities in 2019, the healthcare industry has intensified its AI-based advances by 60%. Moreover, we observed that the healthcare (23% impact), mobility (19% impact), privacy and security (11% impact), and energy sectors (10% impact) have a more significant influence on AI adoption in smart cities. From 2014 to 2021, we examined 133 articles (97% of Scopus and 73% of WoS) in healthcare, education, environment and waste management, agriculture, mobility and smart transportation, risk management, and security. This paper explored how artificial intelligence (AI) is being used in the smart city concept. It is mainly accomplished through an intelligent decision-making process using computational intelligence-based technologies. In order to make lifestyles in cities more comfortable and cost-effective, the city must be smart and intelligent. ![]() By 2050, around 5 billion people (68%) will be residing in cities. According to the United Nations Population Fund, cities accommodated 3.3 billion people (54%) of the global population in 2014. Recently, the population density in cities has increased at a higher pace. Englund, 2020 Huang et al., 2019 Noh et al., 2020 ), traffic monitoring/forecasting( Englund et al., 2021 Ge et al., 2020 Impedovo et al., 2019 Iyer, 2021 Khanna et al., 2018 Liu et al., 2019 Qin et al., 2019 Yi et al., 2019 Zhao et al., 2017 ), routing ( Celaya-Padilla et al., 2019 Hernández-Jiménez et al., 2019 Huang et al., 2019 Perez-Murueta et al., 2019 Shin et al., 2020 ), transportation network services. Englund, 2020 Englund et al., 2021 Garg et al., 2021 Ge et al., 2020 Hernández- Jiménez et al., 2019 Huang et al., 2019 Impedovo et al., 2019 Iyer, 2021 Khanna et al., 2018 Liu et al., 2019 Lv et al., 2020 Noh et al., 2020 Perez-Murueta et al., 2019 Qin et al., 2019 Shin et al., 2020 Thanh et al., 2020 Yi et al., 2019 Zhao et al., 2017 ) based on effective traffic management that include the safe integration of AI-based decision-making( Bai et al., 2019 C. Bai et al., 2019 Celaya- Padilla et al., 2019 Cugurullo, 2020 C.
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