Unterschiede

Hier werden die Unterschiede zwischen zwei Versionen angezeigt.

--- p:ki:zeitreihe [2024/02/06 19:00] – Ralf Kretzschmar
+++ p:ki:zeitreihe [2024/05/02 08:57] (aktuell) – Tscherter, Vincent
@@ Zeile 45: / Zeile 45: @@
   - Starte das untenstehende Programm und studiere die folgenden Punkte (es dauert einen kleinen Moment, bis die Zeitreihe angezeigt wird).
     * Während dem Training wird der Trainingsfehler "loss" (MSE für die +1 Stundenprognose) angezeigt.
-    * Danach wird eine Grafik erzeugt mit
+    * Danach wird eine Grafik für eine Prognosezeitreihe ausgehend von einem Startpunkt erzeugt mit
       * der wahren, beobachteten Zeitreihe (orange)
       * der vorhergesagten Zeitreihe (grün)
-      * dem MAE für die +1, +2, +3, ... + 120 Stundenprognosen (violett)
+    * Zusätzlich wird der MAE für die +1, +2, +3, ... + 120 Stundenprognosen (violett) berechnet. Der MAE wird über mehrere Prognosenzeitreihen ausgehend von mehreren, verschiedenen Startpunkten aus gemittelt.
     * Du kannst nach dem Training zwischen einer Beschreibung des neuronalen Netzes, dem Trainingsfehler und der Vorhersage über die Register ''Modell'', ''Training'' und ''Resultat'' hin und her wechseln.
   - Notiere den MAE für die +72 Stundenprognose, fahre dazu einfach mit der Maus auf die Grafik und suche den MAE für ''x = 72''. {{gem/plain?0=N4XyA#a71e8c87a540f361}}
@@ Zeile 54: / Zeile 54: @@
   - Warum wird der MAE tentenziell immer grösser mit fortschreitender Prognosezeit? Schreibe deine Vermutung in das Textfeld. {{gem/plain?0=N4XyA#5daa8fe086e55930}}
   - Vergleiche deine Antwort mit ++unserer Antwort|\\ \\ Für die Prognosezeit +1 Stunde verwendet das neuronale Netz nur gemessene (beobachtete) Daten. Für die Prognosezeit +2 Stunden wird bereits ein vorhergesagter Wert verwendet, für +3 Stunden zwei etc. Irgendwann basiert die Prognose nur noch auf vorhergesagten Daten und bald einmal auf vorhergesagten Daten, die auf vorhergesagten Daten basieren etc. Daher wird mit fortschreitender Prognosedauer der Fehler immer grösser.\\ \\ ++
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 == ✍ Auftrag 1 – Teil 2 ==
@@ Zeile 79: / Zeile 79: @@
   - Verglichen mit dem MAE in "Auftrag 1 - Teil 1" ist das Resultat besser oder schlechter?{{gem/plain?0=N4XyA#21a4e7574c0199e5}}
   - Wenn du das Programm mehrfach startest, sind die Resultate in etwa gleich gut oder stellst du grössere Unterschiede fest?
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 </WRAP>
 ===== - Dem neuronalen Netzwerk helfen =====
@@ Zeile 102: / Zeile 102: @@
   - Starte das Programm. Ist das Resultat nun besser oder schlechter in den vorangehenden Aufträgen? {{gem/plain?0=N4XyA#d94fcc4114ff694a}}
   - Spiele mit den Parametern etwas herum. Mit wie weinigen ''TIMESERIES_FEATURES'' bekommst du eine MAE für die +72 Stundenprognose von weniger als 0.1 hin? Halte die MAE zusammen mit deiner neuronalen Netz Einstellung im Textfeld fest. {{gem/plain?0=N4XyA#344040d14bb98ac5}}
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 </WRAP>
@@ Zeile 117: / Zeile 117: @@
 In der Defaulteinstellung nutzt das neuronale Netz nur einen einzigen vergangenen Wert der Zeitreihe sowie Cosinus und Sinus der Tagesstunde, d.h. nur 3 Eingangsgrössen.
   - Starte das Programm zwei oder dreimal. Ist das Resultat nun besser oder schlechter in den vorangehenden Aufträgen? Wie vergleicht sich das hier genutzte neuronale Netz mit den zuvor genutzten neuronalen Netzen? {{gem/plain?0=N4XyA#ab0d4297a1770c97}}
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 </WRAP>
@@ Zeile 130: / Zeile 130: @@
 Das neuronale Netz verwendet ausschliesslich vergangene Werte der Zeitreihe als Eingangsgrössen. Obwohl der verwendete Lernalgorithmus ohne Lernrate auskommt, kann dieser in diesem Auftrag zusätzlich mit einer Lernrate "getuned" werden.
   - Starte das Programm zwei oder dreimal. Spiele mit Parametern etwas herum. Versuche, mit möglichst wenigen ''TIMESERIES_FEATURES'' auszukommen. Halte fest, mit welchen Einstellungen du dein bestes Resultat erzielen konntest.{{gem/plain?0=N4XyA#4b7eb6d8feb6e66f}}
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