Electricity load forecasting is one of the hot concerns current electricity market, and many models are proposed to satisfy market participants’ needs. Most have shortcomings large computation or low precision. To address this problem, a novel deep learning data processing ensemble model called SELNet proposed. We performed an experiment with model; consisted two parts: forecasting. In part, au...

Multi-party secure computations are general important procedures to compute any function while keeping the security of private inputs. In this work we ask whether preprocessing can allow low latency (that is, small round) secure multi-party protocols that are universally-composable (UC). In particular, we allow any polynomial time preprocessing as long as it is independent of the exact circuit ...

This paper is concerned with preprocessing techniques for propositional model counting. We have implemented a preprocessor which includes many elementary preprocessing techniques, including occurrence reduction, vivification, backbone identification, as well as equivalence, AND and XOR gate identification and replacement. We performed intensive experiments, using a huge number of benchmarks com...

Trajectory data represents a trace of an object that changes its position in space over time. This kind is complex to handle and analyze, since it generally produced huge quantities, often prone errors generated by the geolocation device, human mishandling, or area coverage limitations. Therefore, there need for software specifically tailored preprocess trajectory data. In this work we propose ...