We have since experimented with 16 time series of differing complexity using neural networks. The performance of the neural networks is compared with that of the Box-Jenkins method. Our experiments indicate that for time series with long memory, both methods produced comparable results. However, for series with short memory, neural networks outperformed the Box-Jenkins model. We discussed the representation ability, the model building process and the applicability of the neural net approach.
Neural networks appear to provide a promising alternative for time series forecasting.
A Concurrent Fast-fits Memory Manager Theodore Johnson, UF, Computer and Inf. Sciences Shared memory multiprocessor systems need efficient dynamic storage allocators,both for system purposes and to support parallel programs. Most memory manager algorithms are based either on a free list, which provides efficient memory use, or on a buddy system, which provides fast allocation and release. In this paper, we present two versions of a memory manager based on the fast fits algorithm, which keeps free memory blocks in a Cartesian tree. A fast fits memory manager provides both efficient memory usage, and fast allocate and release operations.