{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:LEKPHI6HHVEL4FHBGY62VNHS3A","short_pith_number":"pith:LEKPHI6H","canonical_record":{"source":{"id":"1906.01892","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2019-06-05T09:08:58Z","cross_cats_sorted":[],"title_canon_sha256":"e4ed12758fbf4173e94f27c8e87d519fad5f27c5517e19e5b705b86c4a43ac60","abstract_canon_sha256":"9fa1a586b0a09bf00a498b7f6315686930f98a47b70e34797a78b5d2bd67da7f"},"schema_version":"1.0"},"canonical_sha256":"5914f3a3c73d48be14e1363daab4f2d80d72419a1f02a03219994b920c9ad5b7","source":{"kind":"arxiv","id":"1906.01892","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.01892","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"arxiv_version","alias_value":"1906.01892v1","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.01892","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"pith_short_12","alias_value":"LEKPHI6HHVEL","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"LEKPHI6HHVEL4FHB","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"LEKPHI6H","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:LEKPHI6HHVEL4FHBGY62VNHS3A","target":"record","payload":{"canonical_record":{"source":{"id":"1906.01892","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2019-06-05T09:08:58Z","cross_cats_sorted":[],"title_canon_sha256":"e4ed12758fbf4173e94f27c8e87d519fad5f27c5517e19e5b705b86c4a43ac60","abstract_canon_sha256":"9fa1a586b0a09bf00a498b7f6315686930f98a47b70e34797a78b5d2bd67da7f"},"schema_version":"1.0"},"canonical_sha256":"5914f3a3c73d48be14e1363daab4f2d80d72419a1f02a03219994b920c9ad5b7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:05.876346Z","signature_b64":"OIcnvgoFmHMhjeiLHk9bLQbmYB6ORwJCVm/aM11E7WPDqudI0j6+ujiTqjKALDf1HKz+0sbOOFTahWp75xZaAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5914f3a3c73d48be14e1363daab4f2d80d72419a1f02a03219994b920c9ad5b7","last_reissued_at":"2026-05-17T23:44:05.875745Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:05.875745Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.01892","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:44:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ftzfC2j2lfgPFR3QLTa2IJkMSzQCNJrk4PBsCi+E+O4elNOQ9DzD7uVhNbTvnGSjmZ6RfH+pb6uPJZ2kY7LpCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T03:30:00.272099Z"},"content_sha256":"42c20eb95fdbdd632117a7163300a72e4aef4e3d11f665aca5dbb503c3d6b105","schema_version":"1.0","event_id":"sha256:42c20eb95fdbdd632117a7163300a72e4aef4e3d11f665aca5dbb503c3d6b105"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:LEKPHI6HHVEL4FHBGY62VNHS3A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Genetic Random Weight Change Algorithm for the Learning of Multilayer Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.NE","authors_text":"Hong Yongki, Hyongsuk Kim, Mohammad Ibraim Sarker, Yali Nie","submitted_at":"2019-06-05T09:08:58Z","abstract_excerpt":"A new method to improve the performance of Random weight change (RWC) algorithm based on a simple genetic algorithm, namely, Genetic random weight change (GRWC) is proposed. It is to find the optimal values of global minima via learning. In contrast to Random Weight Change (RWC), GRWC contains an effective optimization procedure which are good at exploring a large and complex space in an intellectual strategies influenced by the GA/RWC synergy. By implementing our simple GA in RWC we achieve an astounding accuracy of finding global minima."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.01892","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:44:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0uQHEbo2CDSyybzQxITDvX/C0rpan64d52ON+1ReTz9qaEKFnjnHuo3x6oxYAu8Ik1jyed4NBwsPz5KPObYzAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T03:30:00.272464Z"},"content_sha256":"76986c99d700b8a08e4e62a60ab40ae419d28c852c03a69d9d4c73c646776c87","schema_version":"1.0","event_id":"sha256:76986c99d700b8a08e4e62a60ab40ae419d28c852c03a69d9d4c73c646776c87"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LEKPHI6HHVEL4FHBGY62VNHS3A/bundle.json","state_url":"https://pith.science/pith/LEKPHI6HHVEL4FHBGY62VNHS3A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LEKPHI6HHVEL4FHBGY62VNHS3A/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-30T03:30:00Z","links":{"resolver":"https://pith.science/pith/LEKPHI6HHVEL4FHBGY62VNHS3A","bundle":"https://pith.science/pith/LEKPHI6HHVEL4FHBGY62VNHS3A/bundle.json","state":"https://pith.science/pith/LEKPHI6HHVEL4FHBGY62VNHS3A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LEKPHI6HHVEL4FHBGY62VNHS3A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:LEKPHI6HHVEL4FHBGY62VNHS3A","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"9fa1a586b0a09bf00a498b7f6315686930f98a47b70e34797a78b5d2bd67da7f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2019-06-05T09:08:58Z","title_canon_sha256":"e4ed12758fbf4173e94f27c8e87d519fad5f27c5517e19e5b705b86c4a43ac60"},"schema_version":"1.0","source":{"id":"1906.01892","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.01892","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"arxiv_version","alias_value":"1906.01892v1","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.01892","created_at":"2026-05-17T23:44:05Z"},{"alias_kind":"pith_short_12","alias_value":"LEKPHI6HHVEL","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"LEKPHI6HHVEL4FHB","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"LEKPHI6H","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:76986c99d700b8a08e4e62a60ab40ae419d28c852c03a69d9d4c73c646776c87","target":"graph","created_at":"2026-05-17T23:44:05Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"A new method to improve the performance of Random weight change (RWC) algorithm based on a simple genetic algorithm, namely, Genetic random weight change (GRWC) is proposed. It is to find the optimal values of global minima via learning. In contrast to Random Weight Change (RWC), GRWC contains an effective optimization procedure which are good at exploring a large and complex space in an intellectual strategies influenced by the GA/RWC synergy. By implementing our simple GA in RWC we achieve an astounding accuracy of finding global minima.","authors_text":"Hong Yongki, Hyongsuk Kim, Mohammad Ibraim Sarker, Yali Nie","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2019-06-05T09:08:58Z","title":"Genetic Random Weight Change Algorithm for the Learning of Multilayer Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.01892","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:42c20eb95fdbdd632117a7163300a72e4aef4e3d11f665aca5dbb503c3d6b105","target":"record","created_at":"2026-05-17T23:44:05Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"9fa1a586b0a09bf00a498b7f6315686930f98a47b70e34797a78b5d2bd67da7f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2019-06-05T09:08:58Z","title_canon_sha256":"e4ed12758fbf4173e94f27c8e87d519fad5f27c5517e19e5b705b86c4a43ac60"},"schema_version":"1.0","source":{"id":"1906.01892","kind":"arxiv","version":1}},"canonical_sha256":"5914f3a3c73d48be14e1363daab4f2d80d72419a1f02a03219994b920c9ad5b7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5914f3a3c73d48be14e1363daab4f2d80d72419a1f02a03219994b920c9ad5b7","first_computed_at":"2026-05-17T23:44:05.875745Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:05.875745Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OIcnvgoFmHMhjeiLHk9bLQbmYB6ORwJCVm/aM11E7WPDqudI0j6+ujiTqjKALDf1HKz+0sbOOFTahWp75xZaAg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:05.876346Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.01892","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:42c20eb95fdbdd632117a7163300a72e4aef4e3d11f665aca5dbb503c3d6b105","sha256:76986c99d700b8a08e4e62a60ab40ae419d28c852c03a69d9d4c73c646776c87"],"state_sha256":"63d6721e5fe291581a808ff15e19f5a7aad6519f66778168aa99715fe93496bb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gomhr8+c8Z8eV0conz5UGWW5pGYIS2VDeNqh1LCkag4gPfta6ViRLaRJX00NHtU28wKp9kkuTOZ2knTp/Y/EDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T03:30:00.274336Z","bundle_sha256":"1975437c13746e20128e31d4a93694ed728db5c70f598256136f5518e8e69a01"}}