{"ok":true,"trend":{"id":3045951,"platform":"news","region":"global","key":"published at solar energy - a clustering-based contrastive ensemble lstm model for receiver thermal power prediction in csp plants","title":"Published at Solar Energy - A clustering-based contrastive ensemble LSTM model for receiver thermal power prediction in CSP plants","url":"https://news.google.com/rss/articles/CBMi7AFBVV95cUxOSHhwMHUwOEtJM2xieXZBckNJUFpyWE9EREEwOTlHTy1VZzRZRzV4RWRNRmVZRS1BNnI3UTZPTFBseWZKRWJUbVZCT3gzR1VKNGd6TEZ2OEc4M3NJbGluODV4cVA3VjhMV2tqTmkzWWpHRUI1ZHNjay1LZGw2OTUtRVhkZkNEb3RIMVBLcmJyb3MzNVVZN2VnaGhBMDZHMTBqNmZDaGVzeEF2YVFHTDJtSWFwaFN4X3ZraDRPRkFLNFJLNHJRN1hTRDlqT2Q1SDhBdXZTYzhYS25EZUJVYXJQUmtMZHhzVXJJU3hTRA?oc=5","first_seen":"2026-10-20T23:47:54.326982Z","last_seen":"2026-10-21T11:03:10.374226Z","last_rank":33,"peak_rank":2,"last_volume":null,"peak_volume":0,"seen_count":9,"score":0.5015625,"category_hint":"energy","section":"environment","category":"energy","summary":"A new study published in the journal Solar Energy presents a clustering-based contrastive ensemble LSTM model for predicting receiver thermal power in concentrated solar power plants. The machine learning approach aims to improve operational forecasting for CSP technology. The research comes from work connected to SolarPACES, the international conference network for concentrating solar power and chemical energy systems.","why":"New machine learning research was just published in the Solar Energy journal, drawing attention from the concentrated solar power research community.","tone":"neutral","entities":["Solar Energy (journal)","SolarPACES","concentrated solar power plants"],"summarized_at":"2026-10-21T13:13:07.246198Z","meta":{"via":"scan","lang":"en","term":"solar","source":"SolarPACES","published":"Tue, 20 Oct 2026 22:42:38 GMT"},"nw":null,"promo":null,"kind":null,"importance":null,"hidden":false,"hide_reason":null,"judged_at":null,"title_en":"New AI model predicts solar thermal power in CSP plants","section_name":"Environment","category_name":"Energy","timeline":[{"captured_at":"2026-10-20T23:47:54.326982Z","rank":2,"volume":null},{"captured_at":"2026-10-21T01:09:57.266929Z","rank":3,"volume":null},{"captured_at":"2026-10-21T02:31:55.101910Z","rank":15,"volume":null},{"captured_at":"2026-10-21T03:53:55.062357Z","rank":15,"volume":null},{"captured_at":"2026-10-21T05:15:55.726593Z","rank":15,"volume":null},{"captured_at":"2026-10-21T06:37:53.805597Z","rank":17,"volume":null},{"captured_at":"2026-10-21T08:00:18.152602Z","rank":18,"volume":null},{"captured_at":"2026-10-21T09:22:35.006554Z","rank":22,"volume":null},{"captured_at":"2026-10-21T11:03:10.374226Z","rank":33,"volume":null}],"posts":[{"platform":"news","url":"https://news.google.com/rss/articles/CBMi7AFBVV95cUxOSHhwMHUwOEtJM2xieXZBckNJUFpyWE9EREEwOTlHTy1VZzRZRzV4RWRNRmVZRS1BNnI3UTZPTFBseWZKRWJUbVZCT3gzR1VKNGd6TEZ2OEc4M3NJbGluODV4cVA3VjhMV2tqTmkzWWpHRUI1ZHNjay1LZGw2OTUtRVhkZkNEb3RIMVBLcmJyb3MzNVVZN2VnaGhBMDZHMTBqNmZDaGVzeEF2YVFHTDJtSWFwaFN4X3ZraDRPRkFLNFJLNHJRN1hTRDlqT2Q1SDhBdXZTYzhYS25EZUJVYXJQUmtMZHhzVXJJU3hTRA?oc=5","author":"SolarPACES","title":"Published at Solar Energy - A clustering-based contrastive ensemble LSTM model for receiver thermal power prediction in CSP plants","snippet":null,"posted_at":"2026-10-20T22:42:38Z","likes":null}],"elsewhere":[],"window":"7d"}}