𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Fog forecasting in Cuba. Neural networks versus discriminant analysis

✍ Scribed by Lino R Naranjo-Diaz; Arnaldo P Alfonso

Publisher
John Wiley and Sons
Year
2007
Tongue
English
Weight
330 KB
Volume
2
Category
Article
ISSN
1350-4827

No coin nor oath required. For personal study only.

✦ Synopsis

The relative number of correct forecasts is over 70% for both, which can be considered a good performance. When the learning sample is large enough and nearly equi-probabalistic, the L V Q algorithm provides a greater number of correct forecasts than those obtained via the Fisher discriminant function. However, the results attained via the L V Q algorithm are not steady when the learning sample is far from being equi-probabalistic, because the number of fog cases is much reduced. Until larger samples are available for some regions, it will be necessary to use both methods f o r fog forecasting in Cuba.

📜 SIMILAR VOLUMES

Neural network versus econometric models
Neural network versus econometric models in forecasting inflation
✍ Saeed Moshiri; Norman Cameron 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 201 KB 👁 2 views

Arti®cial neural network modelling has recently attracted much attention as a new technique for estimation and forecasting in economics and ®nance. The chief advantages of this new approach are that such models can usually ®nd a solution for very complex problems, and that they are free from the ass