The Soyang Dam, the largest multipurpose dam in Korea, faces water resource management challenges due to global warming. Global warming increases the duration and frequency of days with high temperatures and extreme precipitation events. Therefore, it is crucial to accurately predict the inflow rate for water resource management because it helps plan for flood, drought, and power generation in the Seoul metropolitan area. However, the lack of hydrological data for the Soyang River Dam causes a physical-based model to predict the inflow rate inaccurately. This study uses nearly 15 years of meteorological, dam, and weather warning data to overcome the lack of hydrological data and predict the inflow rate over two days. In addition, a sequence-to-sequence (Seq2Seq) mechanism combined with a bidirectional long short-term memory (LSTM) is developed to predict the inflow rate. The proposed model exhibits state-of-the-art prediction accuracy with root mean square error (RMSE) of 44.17 m3/s and 58.59 m3/s, mean absolute error (MAE) of 14.94 m3/s and 17.11 m3/s, and Nash–Sutcliffe efficiency (NSE) of 0.96 and 0.94, for forecasting first and second day, respectively.
In this paper, a method is proposed to extract topic keywords of blogs, based on the richness of content. If a blog includes rich content related to a topic word, the word can be considered as a keyword of the blog. For this purpose, a new measure, richness, is proposed, which indicates how much a blog covers the trendy subtopics of a keyword. In order to obtain trendy subtopics of keywords, we use outside topical context data – the web. Since the web includes various and trendy information, we can find popular and trendy content related to a topic. For each candidate keyword, a set of web documents is retrieved by Google, and the subtopics found in the web documents are modelled by a probabilistic approach. Based on the subtopic models, the proposed method evaluates the richness of blogs for candidate keywords, in terms of how much a blog covers the trendy subtopics of keywords. If a blog includes various contents on a word, the word needs to be chosen as one of the keywords of the blog. In the experiments, the proposed method is compared with various methods, and shows better results, in terms of hit count, trendiness and consistency.
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