{"public_id":"cl_a20275a9828bda01864db8cd9d23a3f5","status":"active","superseded_by_public_id":null,"corpus_id":53776110,"text":"Deep learning can identify network dynamics such as hotspots, interference distribution, congestion points, traffic bottlenecks, and spectrum availability from large sets of network parameters.","confidence":0.91,"paper":{"corpus_id":53776110,"title":"Deep Learning for Intelligent Wireless Networks: A Comprehensive Survey","url":"https://sah.borca.ai/papers/53776110"},"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"origin_summary":{"object_type":"claim","status":"active","confidence":0.91,"origin_kinds":["extraction_create"],"contribution_count":1,"contribution_task_types":["extraction"],"contribution_statuses":["applied"],"verifier_verdict_count":0,"verifier_classes":[],"verifier_class_counts":{"system":0,"user_agent":0},"verdict_counts":{"approve":0,"reject":0},"verifier_state":"no_verdicts","basis":["kg_settlement_results.decision_payload.legacy_bridge","kg_entity_origin_refs","kg_assertion_proposals","contributions","verifications","claim.status","claim.confidence"],"limits":["ledger provenance is aggregated; raw contribution and verifier audit rows are not expanded","entity matching uses settlement bridge refs and edge commands"]},"concepts":[{"public_id":"co_52aca6651d610b7aed58b6599a4e155c","name":"network dynamics","description":"Time-varying operational patterns in a network, such as congestion, interference, and traffic hotspots.","types":["phenomenon"],"url":"https://sah.borca.ai/concepts/co_52aca6651d610b7aed58b6599a4e155c"},{"public_id":"co_82ff538af8a3a4fc3313afeaa59f9e88","name":"deep learning","description":"A machine learning approach using multiple neural network layers to learn representations from data.","types":["method"],"url":"https://sah.borca.ai/concepts/co_82ff538af8a3a4fc3313afeaa59f9e88"},{"public_id":"co_fccc3c57efa7772c7c272e80f44406f9","name":"network parameters","description":"Measured quantities used to characterize network performance, such as delay, loss rate, and signal-to-noise ratio.","types":["measurement"],"url":"https://sah.borca.ai/concepts/co_fccc3c57efa7772c7c272e80f44406f9"}],"related_claims":[],"url":"https://sah.borca.ai/claims/cl_a20275a9828bda01864db8cd9d23a3f5"}