Pith Number

pith:3YKV7I2H

pith:2026:3YKV7I2H34WR43B4NPXWNM4OOY

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DSPR: Dual-Stream Physics-Residual Networks for Trustworthy Industrial Time Series Forecasting

Guoqing Wang, Pengwei Yang, Tianyu Li, Yeran Zhang

DSPR decouples stable temporal patterns from regime-dependent residual dynamics to forecast industrial time series with high accuracy and physical consistency.

arxiv:2604.07393 v2 · 2026-04-08 · cs.LG · cs.AI

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Claims

C1strongest claim

Experiments on four industrial benchmarks spanning heterogeneous regimes demonstrate that DSPR consistently improves forecasting accuracy and robustness under regime shifts while maintaining strong physical plausibility. It achieves state-of-the-art predictive performance, with Mean Conservation Accuracy exceeding 99% and Total Variation Ratio reaching up to 97.2%.

C2weakest assumption

That the physical priors embedded in the Physics-Guided Dynamic Graph accurately reflect true regime-dependent interaction structures without introducing bias or suppressing valid correlations, and that the Adaptive Window module reliably estimates flow-dependent transport delays from data alone.

C3one line summary

DSPR decouples statistical temporal evolution from physics-informed residual dynamics via an adaptive window for transport delays and a physics-guided dynamic graph to achieve accurate, physically plausible forecasts on industrial benchmarks with over 99% mean conservation accuracy.

Receipt and verification

First computed	2026-05-20T00:03:10.708513Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

de155fa347df2d1e6c3c6bef66b38e761ddcb789559333358ae5fcf39bdc5df8

Aliases

arxiv: 2604.07393 · arxiv_version: 2604.07393v2 · doi: 10.48550/arxiv.2604.07393 · pith_short_12: 3YKV7I2H34WR · pith_short_16: 3YKV7I2H34WR43B4 · pith_short_8: 3YKV7I2H

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/3YKV7I2H34WR43B4NPXWNM4OOY \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: de155fa347df2d1e6c3c6bef66b38e761ddcb789559333358ae5fcf39bdc5df8

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "6c3c87eb83c105ccc080e77f1f952d2660022404e39510316e379225a09050f7",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-04-08T06:21:10Z",
    "title_canon_sha256": "d9aa50c9a9c7444dc991a01e89555001dcfc9bbc3253776bb0cea9be387ad1e2"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.07393",
    "kind": "arxiv",
    "version": 2
  }
}