www.bing.com/ck/a?!&&p=f1f8d427b75d5e96caf764f479187024f2add643cb87172d722a496462b172e6JmltdHM9MTc3MjQ5NjAwMA&ptn=3&ver=2&hsh=4&fclid=14f42296-b23e-670d-04f0-3584b3876611&u=a1aHR0cHM6Ly93d3cud2VhdGhlci1mb3JlY2FzdC5jb20vbG9jYXRpb25zL05ldy1HbGFzZ293L2ZvcmVjYXN0cy9sYXRlc3Q&ntb=1
2 days ago · New Glasgow Weather Photos See weather photos from Nova Scotia, Canada. Upload your own New Glasgow weather image: Upload
www.bing.com/ck/a?!&&p=d9e6f4f87dc6723f5edd040185bc822ad928bd14ee0a15dbb77fd3cc4ec1ecf1JmltdHM9MTc3MjQ5NjAwMA&ptn=3&ver=2&hsh=4&fclid=32140973-9763-6796-03cd-1e6196cb6600&u=a1aHR0cHM6Ly93d3cucmV1dGVycy5jb20vYnVzaW5lc3MvZmluYW5jZS8&ntb=1
1 day ago · Financial technology firm Chime forecast 2026 revenue above Wall Street estimates on Wednesday, helped by strong demand for its digital banking products and resilient consumer spending.
arxiv.org/abs/1403.7001v1
A novel method for predicting time series is described and demonstrated. This method inputs time series data points and outputs multiple "spaghetti" functions from which predictions can be made. Spaghetti prediction has desirable properties that are...
github.com/nityansuman/warren
Web app to predict closing stock prices in real time using Facebook's Prophet time series algorithm with a multi-variate, single-step time series forecasting strategy. (⭐ 336)
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4 days ago · View Microsoft Corporation MSFT stock quote prices, financial information, real-time forecasts, and company news from CNN.
en.wikipedia.org/wiki/List_of_countries_by_GDP_%28PPP%29
GDP (PPP) means gross domestic product based on purchasing power parity. This article includes a list of countries by their forecast estimated GDP (PPP)
arxiv.org/abs/2510.18133v1
We discuss the utility of applying clustering as a preprocessing step for identifying subseasonal to seasonal forecasts of opportunity of coastal sea level using convolutional neural networks (CNNs). Clustering leverages potential covariance among po...
www.bing.com/ck/a?!&&p=84f145607e9549f079c8baa284114849892ba25f03c2993814f15a548d7c35b5JmltdHM9MTc3MjQ5NjAwMA&ptn=3&ver=2&hsh=4&fclid=10287227-ff9f-64a2-05b4-6535fe2065b2&u=a1aHR0cHM6Ly9uZXdzLm1pdC5lZHUvMjAyNS9tYWtpbmctY2xlYW4tZW5lcmd5LWludmVzdG1lbnRzLW1vcmUtc3VjY2Vzc2Z1bC0xMjEy&ntb=1
Dec 12, 2025 · New research emphasizes the importance of well-validated models and forecasting tools in evaluating choices for investments in clean energy technologies and policies by governments and …
arxiv.org/abs/2306.15664v3
In recent years, badminton analytics has drawn attention due to the advancement of artificial intelligence and the efficiency of data collection. While there is a line of effective applications to improve and investigate player performance, there are...
arxiv.org/abs/2012.11935v1
This paper considers the Split-Then-Combine (STC) approach (Arroyo and de Juan, 2014) to combine forecasts inside the simplex space, the sample space of positive weights adding up to one. As it turns out, the simplicial statistic given by the center...
arxiv.org/abs/1407.3652v1
We present a new Monte-Carlo methodology to forecast the crude oil production of Norway and the U.K. based on a two-step process, (i) the nonlinear extrapolation of the current/past performances of individual oil fields and (ii) a stochastic model of...
arxiv.org/abs/2509.09176v2
The convergence of quantum-inspired neural networks and deep reinforcement learning offers a promising avenue for financial trading. We implemented a trading agent for USD/TWD by integrating Quantum Long Short-Term Memory (QLSTM) for short-term trend...
arxiv.org/abs/2005.04557v3
In this paper, we propose a novel multi-variate algorithm using a triple-regression methodology to predict the airborne-pollen allergy season that can be customized for each patient in the long term. To improve the prediction accuracy, we first perfo...
arxiv.org/abs/1903.06667v3
In this paper, we divide the globe into a hexagonal grid and we extracted time series of daily fire counts from each cell to estimate and analyze worldwide fire season severity (FSS), here defined as the accumulated fire detections in a season. The c...
arxiv.org/abs/2210.16382v1
We present a new method for creating a model consensus to improve real-time hurricane track prediction. The method is based on the statistical fitting of historic numerical model track forecasts to the observed storm positions and learning from their...
github.com/hafs-community/HAFS
Hurricane Analysis and Forecast System (⭐ 52)
github.com/open-meteo/open-meteo
Free Weather Forecast API for non-commercial use (⭐ 4902)
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Aug 27, 2025 · 20 years ago, Hurricane Katrina tore through the southeastern United States, causing much destruction. This video features thoughts from NOAA staff who were involved in the forecasting …
arxiv.org/abs/1709.01907v1
Reliable uncertainty estimation for time series prediction is critical in many fields, including physics, biology, and manufacturing. At Uber, probabilistic time series forecasting is used for robust prediction of number of trips during special event...
arxiv.org/abs/1301.1111v1
This document is another installment in a series of near real-time weekly influenza forecasts made during the 2012-2013 influenza season. Here we present some of the results of forecasts initiated following assimilation of observations for Week 52 (i...
