[ad_1] Introduction Time series forecasting has been widely used in various fields such as finance, economics, and business to predict future values based on historical data. In the context of economic indicators, time series forecasting…
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[ad_1] Introduction In recent years, deep learning techniques have shown great potential in a wide range of applications including image recognition, natural language processing, and autonomous driving. One area where deep learning has made significant…
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[ad_1] Introduction In today’s highly competitive and volatile business environment, supply chain resilience has become a critical factor for the success of organizations. The ability to predict and mitigate potential risks within the supply chain…
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[ad_1] **Introduction:** In the age of social media and online reviews, companies are increasingly interested in monitoring and analyzing public opinion in order to measure and improve their brand equity. Opinion mining, also known as…
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[ad_1] Introduction With the increasing amount of digital communication, the issue of spam emails has become a significant problem for individuals, businesses, and organizations. Spam emails are unsolicited messages sent in bulk, often with the…
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[ad_1] Introduction: The insurance industry is one of the most competitive sectors in the financial services industry, with companies constantly looking for ways to attract and retain customers. Customer Lifetime Value (CLV) prediction is a…
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[ad_1] Introduction In recent years, the increasing use of social media has provided an unprecedented amount of real-time data that can be analyzed to understand public sentiment during crises. Sentiment analysis, a branch of natural…
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[ad_1] Introduction In recent years, online dating platforms have become increasingly popular, with millions of users seeking to find potential partners through these platforms. With the vast number of users and profiles on these platforms,…
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[ad_1] Introduction Anomaly detection in water distribution networks is a critical area of research that aims to identify abnormal events or behaviors in the network that could potentially indicate leaks, bursts, or other issues that…
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[ad_1] Introduction: Traffic congestion is a major issue that affects urban areas worldwide, leading to increased travel times, fuel consumption, and greenhouse gas emissions. In recent years, the advent of deep learning techniques has shown…
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