3results about How to "Small standard deviation" patented technology

The application provides an aluminum profile pre-aging stability treatment method and belongs to the technical field of aluminum profile production. A data set is established through cross-section thickness scanning, a multi-scale asymptotic expansion homogenization algorithm and thermodynamic path integral Monte Carlo simulation are used to predict a temperature field and precipitate phase evolution, a double-layer game model is used to optimize partition heating power distribution, temperature history synchronous control is realized through dynamic adjustment of a model prediction controller, an artificial intelligence organization uniformity evaluation model and a learning rate dynamic adjustment mechanism are combined to realize online optimization, and finally, process parameters are adjusted through mechanical property detection feedback, so that the technical problem of large differences in precipitate phase organization states caused by uneven temperature distribution in different cross-section thickness regions during the pre-aging process of the aluminum profile is solved.

A negative electrode for an electrochemical device and an electrochemical device including the same are provided. The negative electrode for the electrochemical device comprises: a current collector; and a negative electrode active material layer present on the current collector, wherein the negative electrode active material layer comprises particles containing a silicon-based active material, a linearly conductive material, and a binder for the particles, wherein the dispersion of the particles within the negative electrode active material layer is 1 × 10⁻⁶. ‑2 Up to 10×10 ‑2 The standard deviation of particle dispersion is 1×10⁻⁶. ‑3 Up to 4×10 ‑3 The volume expansion rate of the negative electrode active material layer is 3% to 30%.

The application provides an interval event matching method and system of a content-based publish / subscribe system, through constructing a predicate disjoint set and an optimized partition model thereof, and integrating a learning index of a range query recursive model index in each partition, high-speed, stable and verifiable matching of events to a subscription set under multi-attribute interval predicates is realized; in particular, the traditional memory-intensive matching is reconstructed into a calculation-intensive process mainly based on model reasoning, while correctness and completeness are ensured, average latency is reduced and long tail delay is inhibited, and key modules such as partition and coverage optimization, model training and online reasoning, error boundary control and limited correction, and accurate back matching of residual set subscription are included.