参数设计学:把昂贵调用最多降一个量级的参数组织方法 / Parameter Design Science: Organizing Parameters to Cut Expensive Calls by up to an Order of Magnitude
White paper (Chinese and English editions, v1.2.1 — revised after a rigorous flagship-model review). After a model is fixed, an upstream and frequently overlooked determinant of computational cost is how its parameters are organized. Two of four failure mechanisms carry measured ledgers on a 12-condition parameter chain (missing benchmark accounting: 56% single-layer / 71.4% three-layer; transcendentalization: 92.9% expensive-call reduction); two are asserted from practice and flagged as such. Seven tools (two-half representation, projection operators, equipoints with deviation readings, anchor order, algebraization, layering, status/binding metadata), an audit procedure, an explicit relation-to-established-techniques section (memoization/CSE/symbolic simplification/constraint elimination as relatives), and two runnable Python demos with equivalence checks. Scope and limitations stated in §5.1/§9.
Authors
- Qin Qin (ORCID: https://orcid.org/0000-0002-4046-0306)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-11-05
- DOI
- https://doi.org/10.5281/zenodo.23979000
- Primary Topic
- Optimal Experimental Design Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00