Incidence and prediction of cutaneous leishmaniasis cases and its related factors in an endemic area of Southeast Morocco: time series analysis

Acta Tropica, Journal Year: 2025, Volume and Issue: unknown, P. 107579 - 107579

Published: March 1, 2025

Language: Английский

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Research on Cargo Volume Prediction of Logistics Networks Based on Time Series Processing and Directed Acyclic Graph Model

Highlights in Business Economics and Management, Journal Year: 2025, Volume and Issue: 51, P. 178 - 187

Published: Feb. 27, 2025

With the rapid development of e-commerce and logistics industry, accurately predicting cargo volume at sorting centers to improve efficiency service quality system has become an important research topic. In response this, this paper conducts a comprehensive study. First, operation data from platform are obtained through competition's official website, followed by preprocessing, including time series conversion, wavelet transform denoising, white noise detection, differencing smoothing, stationarity tests, center into stationary series. Next, ARIMA model is applied forecast for next 30 days. Furthermore, directed acyclic graph constructed, historical used calculate node strength. Future transportation route changes also considered update strength solve state transition weight matrix. Ultimately, using model, overall prediction accuracy reached over 80%, with average predicted 50677.8kg December, total 1520334kg entire month December. This holds significant importance in study forecasting within networks.

Language: Английский

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Optimization model for mineral composition data analysis and its application in jade classification

Applied Mathematics and Nonlinear Sciences, Journal Year: 2024, Volume and Issue: 9(1)

Published: Jan. 1, 2024

Abstract The classification of jade grade has always been a very critical part the industry, and improving accuracy is great significance to sustainable development industry. study constructs mineral identification model based on Raman spectroscopy + PCA through principal component analysis analyzes data grades constituents. actual performance this paper’s explored by comparing its effectiveness with other algorithmic models in parameters. paper feasible classifying four Hetian (seed material, gobi shanliushui shanmu material). Green dense jade’s main minerals are <unk>-quartz few minerals, including albite, hematite, graphite, tourmaline. compositions sample SiO 2 , Al O 3 K O. overall Xinjiang Hotan 97.9%, which significantly higher than that KNN algorithm SVM algorithm. total each parameter 85, 60 62 algorithm, high.

Language: Английский

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A neural network-based model for cross-border e-commerce supply chain demand forecasting and inventory optimization

Applied Mathematics and Nonlinear Sciences, Journal Year: 2024, Volume and Issue: 9(1)

Published: Jan. 1, 2024

Abstract The development of the Internet makes e-commerce transaction scale in total global trade share grow year by year, and cross-border has become an important growth point virtue its unique advantages. In this paper, ARIMA model is used to obtain time series demand change a supply chain, results are input into LSTM realize construction chain forecasting model. ABC inventory classification method economic lot ordering as basis for establishment control strategies multi-cycle models. Taking sales data WT enterprise from May 2022 2023 example, effectiveness ARIMA-LSTM analyzed, optimization multi-period verified. relative error fluctuation range between [-0.1,0.2], chain’s monthly forecast MAPE value only 0.0135. After using model, annual average reduced 178.42 tons, cost 0.09*10 8 yuan. Relying on neural networks can achieve accurate prediction optimize inventory.

Language: Английский

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Research on competition score prediction based on GA-BP neural network model and RBP inverse neural network model

2022 International Conference on Electronics and Devices, Computational Science (ICEDCS), Journal Year: 2024, Volume and Issue: unknown, P. 562 - 566

Published: Sept. 23, 2024

Language: Английский

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