{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:VMEOR2S7725QWQ5JLAXVERFHNQ","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":"acff7bac16de7b50ab4bb6e3267718302865435122992da74cfcff39ed8e16d4","cross_cats_sorted":["math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2018-09-27T16:07:16Z","title_canon_sha256":"1dc88fcccf86b994377e0cfa0b3fd0b54fc65b3aec1193687ab4b19d28bc2298"},"schema_version":"1.0","source":{"id":"1810.08652","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.08652","created_at":"2026-05-18T00:02:43Z"},{"alias_kind":"arxiv_version","alias_value":"1810.08652v1","created_at":"2026-05-18T00:02:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.08652","created_at":"2026-05-18T00:02:43Z"},{"alias_kind":"pith_short_12","alias_value":"VMEOR2S7725Q","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"VMEOR2S7725QWQ5J","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"VMEOR2S7","created_at":"2026-05-18T12:32:59Z"}],"graph_snapshots":[{"event_id":"sha256:c6da3efdf753fa2849d4e891bddac64472878b3995d45836993d38739e86c312","target":"graph","created_at":"2026-05-18T00:02:43Z","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 optimized extreme learning machine- (ELM-) based method for power system transient stability prediction (TSP) using synchrophasors is presented in this paper. First, the input features symbolizing the transient stability of power systems are extracted from synchronized measurements. Then, an ELM classifier is employed to build the TSP model. And finally, the optimal parameters of the model are optimized by using the improved particle swarm optimization (IPSO) algorithm. The novelty of the proposal is in the fact that it improves the prediction performance of the ELM-based TSP model by us","authors_text":"Guangyu Na, Guoqing Li, Tie Li, Yang Li, Yanjun Zhang","cross_cats":["math.OC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2018-09-27T16:07:16Z","title":"Optimized Extreme Learning Machine for Power System Transient Stability Prediction Using Synchrophasors"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.08652","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":"sha256:884a2e325316ae4cca552a8026f63514db721a9e3866c0b0f61748bbb11494f4","target":"record","created_at":"2026-05-18T00:02:43Z","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":"acff7bac16de7b50ab4bb6e3267718302865435122992da74cfcff39ed8e16d4","cross_cats_sorted":["math.OC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2018-09-27T16:07:16Z","title_canon_sha256":"1dc88fcccf86b994377e0cfa0b3fd0b54fc65b3aec1193687ab4b19d28bc2298"},"schema_version":"1.0","source":{"id":"1810.08652","kind":"arxiv","version":1}},"canonical_sha256":"ab08e8ea5ffebb0b43a9582f5244a76c1c289dfd5273d3f2dfae3ec4282ed93f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ab08e8ea5ffebb0b43a9582f5244a76c1c289dfd5273d3f2dfae3ec4282ed93f","first_computed_at":"2026-05-18T00:02:43.899049Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:02:43.899049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vHJf9YvZWMkgWSeZneQk9sJwVHIWV1yWMioLsW0lmrQ+ZDds768KJY1Ca4LSaTMYuGJp46sXCNx6T8J3fYWABQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:02:43.899509Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.08652","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:884a2e325316ae4cca552a8026f63514db721a9e3866c0b0f61748bbb11494f4","sha256:c6da3efdf753fa2849d4e891bddac64472878b3995d45836993d38739e86c312"],"state_sha256":"b6a06dcc30127ef7b0a3fb29c495032d077999105bbbac7d56b2545528cff44a"}