AI ninu Idanwo Ipese Ipese

Awọn idahun ati awọn alaye han bi o ṣe n mu ibeere naa.

1. Kini ibi-afẹde akọkọ ti asọtẹlẹ ibeere eletan ti AI ni awọn ẹwọn ipese?
   • Lati ṣe asọtẹlẹ iye ti ọja kọọkan yoo ta, nibo, ati nigbawo
   • Lati ṣe apẹrẹ apoti ọja tuntun
   • Lati kọ ẹda tita fun awọn igbega
   • Lati rọpo gbogbo awọn oṣiṣẹ ile itaja
2. Iru iṣoro wo ni ipa-ọna ati awọn ipinnu akojo oja ni igbagbogbo ti a ṣe bi?
   • Awọn iṣoro ipinya aworan
   • Awọn iṣoro iṣapeye mathematiki (fun apẹẹrẹ, awọn eto odidi-odidi)
   • Awọn iṣoro idanimọ ọrọ
   • Awọn iṣoro amoro lairotẹlẹ
3. What type of demand output does the cited Zalando replenishment study integrate into inventory optimization?
   • A guaranteed exact unit count for every future day
   • An unqualified social-media popularity score
   • Probabilistic forecasts that represent uncertainty in future demand
   • A fixed rule that ignores the forecast distribution
4. What does a digital twin represent in a supply-network scenario?
   • A guarantee that every sensor is live and synchronized at all times
   • A second physical warehouse that automatically executes every decision
   • A model that proves a disruption cannot occur
   • A virtual representation of a physical system that can be linked with data for modeling or simulation
5. What can make an AI-enabled supply chain more resilient during a disruption?
   • Visibility, scenario planning, and the ability to adjust decisions as conditions change
   • A guarantee that demand will never change
   • Removing all human operators
   • Using only historical averages
6. How should observed supply-chain outcomes be used in a forecast feedback loop?
   • Assume every new observation automatically improves the model
   • Evaluate forecast errors and consider validated updates using appropriate outcome data
   • Retrain continuously without checking data quality or performance
   • Treat each forecast as a confirmed future outcome
7. Which replenishment policy did the cited e-commerce study extend?
   • A proportional-derivative controller for motor speed
   • A shortest-path algorithm for vehicle routing
   • The (R, s, Q) policy, adding variables for initial replenishment and a policy horizon
   • A fixed moving-average demand forecast
8. Why combine forecasts with an optimization model?
   • They are identical tasks
   • Optimization removes all uncertainty
   • Forecasting automatically places orders
   • A forecast estimates future conditions, while optimization chooses actions under constraints