{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:CPJKGDKWAOMISBJRMQSZOG5DYE","short_pith_number":"pith:CPJKGDKW","schema_version":"1.0","canonical_sha256":"13d2a30d5603988905316425971ba3c12bc6049997517222da2d67f18513e336","source":{"kind":"arxiv","id":"2409.10455","version":1},"attestation_state":"computed","paper":{"title":"Quantile Fourier regressions for decision making under uncertainty","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Arash Khojaste, Geoffrey Pritchard, Golbon Zakeri","submitted_at":"2024-09-16T16:46:08Z","abstract_excerpt":"Weconsider Markov decision processes arising from a Markov model of an underlying natural phenomenon. Such phenomena are usually periodic (e.g. annual) in time, and so the Markov processes modelling them must be time-inhomogeneous, with cyclostationary rather than stationary behaviour. We describe a technique for constructing such processes that allows for periodic variations both in the values taken by the process and in the serial dependence structure. We include two illustrative numerical examples: a hydropower scheduling problem and a model of offshore wind power integration."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2409.10455","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"math.OC","submitted_at":"2024-09-16T16:46:08Z","cross_cats_sorted":[],"title_canon_sha256":"20a0300956184003730228f5b163e58c86bee4db4fbaae4216b69056cdec6a17","abstract_canon_sha256":"316d0f9bc0f24d2ef18224041639de692817ac73d8e54167e83f70c067f1b383"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:07:40.383853Z","signature_b64":"Pe1tCfS1yQ62e6+Z3TW+O3MhvdLJSABzfcWJTi5doSxafjZtmNTMm/XSjZIMdvy43zFRQaXJOEz4IEI+wtF4CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"13d2a30d5603988905316425971ba3c12bc6049997517222da2d67f18513e336","last_reissued_at":"2026-07-05T09:07:40.383370Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:07:40.383370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Quantile Fourier regressions for decision making under uncertainty","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Arash Khojaste, Geoffrey Pritchard, Golbon Zakeri","submitted_at":"2024-09-16T16:46:08Z","abstract_excerpt":"Weconsider Markov decision processes arising from a Markov model of an underlying natural phenomenon. Such phenomena are usually periodic (e.g. annual) in time, and so the Markov processes modelling them must be time-inhomogeneous, with cyclostationary rather than stationary behaviour. We describe a technique for constructing such processes that allows for periodic variations both in the values taken by the process and in the serial dependence structure. We include two illustrative numerical examples: a hydropower scheduling problem and a model of offshore wind power integration."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.10455","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2409.10455/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2409.10455","created_at":"2026-07-05T09:07:40.383430+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.10455v1","created_at":"2026-07-05T09:07:40.383430+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.10455","created_at":"2026-07-05T09:07:40.383430+00:00"},{"alias_kind":"pith_short_12","alias_value":"CPJKGDKWAOMI","created_at":"2026-07-05T09:07:40.383430+00:00"},{"alias_kind":"pith_short_16","alias_value":"CPJKGDKWAOMISBJR","created_at":"2026-07-05T09:07:40.383430+00:00"},{"alias_kind":"pith_short_8","alias_value":"CPJKGDKW","created_at":"2026-07-05T09:07:40.383430+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/CPJKGDKWAOMISBJRMQSZOG5DYE","json":"https://pith.science/pith/CPJKGDKWAOMISBJRMQSZOG5DYE.json","graph_json":"https://pith.science/api/pith-number/CPJKGDKWAOMISBJRMQSZOG5DYE/graph.json","events_json":"https://pith.science/api/pith-number/CPJKGDKWAOMISBJRMQSZOG5DYE/events.json","paper":"https://pith.science/paper/CPJKGDKW"},"agent_actions":{"view_html":"https://pith.science/pith/CPJKGDKWAOMISBJRMQSZOG5DYE","download_json":"https://pith.science/pith/CPJKGDKWAOMISBJRMQSZOG5DYE.json","view_paper":"https://pith.science/paper/CPJKGDKW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.10455&json=true","fetch_graph":"https://pith.science/api/pith-number/CPJKGDKWAOMISBJRMQSZOG5DYE/graph.json","fetch_events":"https://pith.science/api/pith-number/CPJKGDKWAOMISBJRMQSZOG5DYE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CPJKGDKWAOMISBJRMQSZOG5DYE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CPJKGDKWAOMISBJRMQSZOG5DYE/action/storage_attestation","attest_author":"https://pith.science/pith/CPJKGDKWAOMISBJRMQSZOG5DYE/action/author_attestation","sign_citation":"https://pith.science/pith/CPJKGDKWAOMISBJRMQSZOG5DYE/action/citation_signature","submit_replication":"https://pith.science/pith/CPJKGDKWAOMISBJRMQSZOG5DYE/action/replication_record"}},"created_at":"2026-07-05T09:07:40.383430+00:00","updated_at":"2026-07-05T09:07:40.383430+00:00"}