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DaRUS

(University of Stuttgart)

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File Type: Data

601 to 610 of 12,526 Results

CBSD_Pypesto_Parameters_optimization_dictionary.json Mar 21, 2025 - DLC1 knockdown in EMT in MCF10A cells JSON - 931 B - MD5: b79c3cfb6b6ab7ceda22fd319c5337db Dictionary containing the optimized parameter values
GP_00.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 553.7 KB - MD5: 21610e5f675a9c616922962e836f1742
GP_01.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 560.3 KB - MD5: 6a5507abfa6ca21b864210f8a9a720eb
GP_02.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 546.2 KB - MD5: 1790b4a412ea8c0235809e20538e539f
GP_03.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 546.2 KB - MD5: 7a0b79d1f887ac6dd9ce1c7d75fa8b28
GP_04.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 555.3 KB - MD5: cce918a488a3074f5ab1ba3d0fe7b344
LHS_00.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 1.3 MB - MD5: a6cbae1b4477d3e08c2775ccf15d5c68
LHS_01.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 7.0 MB - MD5: 0287865a26350178b258a19a9103dc6a
MOEAD_00.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 556.5 KB - MD5: 00ced999c97245139b970e7b95765ce5
MOEAD_01.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 6.6 MB - MD5: 7e6985db79cb7fa0a1262ff2dcd593e5

CBSD_Pypesto_Parameters_optimization_dictionary.json

Mar 21, 2025 - DLC1 knockdown in EMT in MCF10A cells

JSON - 931 B -

Dictionary containing the optimized parameter values

GP_00.json

Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.

JSON - 553.7 KB -

GP_01.json

Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.

JSON - 560.3 KB -

GP_02.json

Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.