While the traditional genetic algorithms are capable of forecasting house prices, they often suffer from premature convergence, which adversely affects the reliability of the forecasts. To address this issue, the research employs a genetic-particle s...
Accurate prediction of gold prices is crucial for investment decision-making and national risk management. The time series data of gold prices exhibits random fluctuations, non-linear characteristics, and high volatility, making prediction extremely ...
With the transition to a global green low-carbon economy, the urgency for digital transformation in the port and shipping industry has become increasingly prominent in making enterprises more efficient and sustainable. This study focuses on how Chine...
This study aims to conduct a comprehensive and in-depth analysis of the marketing performance of e-commerce live broadcast platforms based on big data management technology and deep learning. Firstly, by synthesizing large-scale datasets and surveys,...
International journal of health geographics
Apr 28, 2025
BACKGROUND: Illicit kidney trade networks, operating globally, involve intricate interactions among various players, most notably buyers, sellers, brokers, and surgeons. A comprehensive understanding of these trade networks is, however, hindered by t...
Computer methods and programs in biomedicine
Apr 24, 2025
BACKGROUND: Accurate prediction of hospital emergency department (ED) patient visits and acuity levels have potential to improve resource allocation including manpower planning and hospital bed allocation. Internet search data have been used in medic...
The complexities of stock price data, characterized by its nonlinearity, non-stationarity, and intricate spatiotemporal patterns, make accurate prediction a substantial challenge. To address this, we propose the DCA-BiLSTM model, which combines dual-...
Continuous access to up-to-date food price data is crucial for monitoring food security and responding swiftly to emerging risks. However, in many food-insecure countries, price data is often delayed, lacks spatial detail, or is unavailable during cr...
This study compares the precision and interpretability of two automated valuation models for evaluating the real estate market in the Santiago Metropolitan Region of Chile: machine learning algorithms, specifically LightGBM, and hedonic prices with s...
The Stability of the economy is always a great challenge across the world, especially in under developed countries. Many researchers have contributed to forecasting the Stock Market and controlling the situation to ensure economic stability over the ...
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