Showing 2,321 - 2,340 results of 7,744 for search 'significantly ((((linear decrease) OR (we decrease))) OR (((teer decrease) OR (greater decrease))))', query time: 0.42s Refine Results
  1. 2321

    Proposed model of energy management for SREH. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  2. 2322

    Technical features of PV module. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  3. 2323

    Cooling power of SREH in Case Study-III. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  4. 2324

    Hourly power generation of solar and wind. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  5. 2325

    Cooling power of SREH in Case Study-IV. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  6. 2326

    Technical features of PHEV battery. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  7. 2327

    Electrical power of SREH in Case Study-III. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  8. 2328

    Heating power of SREH in Case Study-III. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  9. 2329

    Conceptual framework of REH under study. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  10. 2330

    Energy hub architecture. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  11. 2331

    Electricity and gas prices. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  12. 2332

    Technical features of central devices. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  13. 2333

    Results for Case Study-I. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  14. 2334

    Technical features of wind turbine. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  15. 2335

    Heating power of SREH in Case Study-IV. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  16. 2336

    Electrical power of SREH in Case Study-IV. by Nouman Qamar (21511939)

    Published 2025
    “…This work proposed a stochastic model for REH using mixed integer linear programming (MILP) to optimally handle the associated uncertainties of RES and PEHVs, which was then solved using GAMS software. …”
  17. 2337

    Participant interview topics. by Lex D. de Jong (22138778)

    Published 2025
    “…Outcomes were evaluated with a multilevel linear regression analysis at baseline, 2 weeks, 3 months and 6 months. …”
  18. 2338

    The participants’ baseline characteristics. by Lex D. de Jong (22138778)

    Published 2025
    “…Outcomes were evaluated with a multilevel linear regression analysis at baseline, 2 weeks, 3 months and 6 months. …”
  19. 2339

    Alignment of the Taxane binding pocket sequences. by Jacopo Zattoni (21702634)

    Published 2025
    “…The results were analyzed using a consensus method to increase their reliability. We found that the amoeba’s mitotic tubulins show a significant number of changes that are expected to decrease their affinity for tubulin-targeting compounds. …”
  20. 2340

    Rank of mutation fitness. by Zhong-yi Lei (22552944)

    Published 2025
    “…Retrospective validation demonstrated that CoVPF achieved 20.7% higher accuracy compared to previous study. Furthermore, we found that accounting for epistasis was critical, as ignoring epistasis led to a 43% decrease in forecasting accuracy. …”