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Supplement S1: Energy Storage Capability Classification with Response and Energy Memory

Year: 2026

Type: article

Abstract: Supplement S1 to the conference paper "Energy Storage Capability Classification with Response and Energy Memory" (PE0053). Contents: (S1.1) scope of the supplement; (S1.2) data generator and class-dependent parameter ranges; (S1.3) resource split of 32 training, 8 validation and 10 test resources; (S1.4) the thirteen candidate configurations and their cumulative simplification scheme; (S1.5) acceptance criteria relative to the five-seed O64 validation mean; (S1.6) complete validation results for all candidates; (S1.7) parameter-counting definitions (stored, active, dormant, effective); (S1.8) training recipe including optimizer, schedule, batch size, clipping and seeds 11/22/33/44/55; (S1.9) timing procedure with the measurement environment and warm-up protocol; (S1.10) complete test results; (S1.11) parameter and latency savings. The supplement supports the reproducibility of the selection procedure reported in Tables II-V and Fig. 2 of the paper.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.24047110

Authors: Lin, Xiaoze, Zhu, Chao, Nie, Jianbo, Wu, Wenjun, Zhang, Youbing

Institutions: Zhejiang University of Technology, State Grid Zhejiang Electric Power Company (China)

Language: English

Topic: Advanced Memory and Neural Computing

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: green

OpenAlex ID: W7225583438

FWCI:

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