In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...

This repository contains a Python-based project for real-time healthcare monitoring, focusing on forecasting patient heart rates using the ARIMA (AutoRegressive Integrated Moving Average) model. The ...

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Climate change has significantly impacted vulnerable communities globally, with rising temperatures caused by greenhouse gas emissions accelerating global Sea Level Rise (SLR), threatening coastal ...

Developers can now use Pydantic's mcp-run-python server, distributed via JSR, to allow AI agents to execute Python code with automatic dependency handling in isolation. It addresses a frequent ...

There are numerous ways to run large language models such as DeepSeek, Claude or Meta's Llama locally on your laptop, including Ollama and Modular's Max platform. But if you want to fully control the ...

This paper presents a comparative study of ARIMA and Neural Network AutoRegressive (NNAR) models for time series forecasting. The study focuses on simulated data generated using ARIMA(1, 1, 0) and ...

Abstract: ARIMA model is a statistical method for shortterm prediction of stationary time series, and in the specific modeling process, AIC and BIC criteria are generally used to select the number of ...

ABSTRACT: The energy sector is the second largest emitter of greenhouse (GHG) gases in Kenya, emitting about 31.2% of GHG emissions in the country. The aim of this study was to model Kenya’s GHG ...