Search alternatives:
action optimization » reaction optimization (Expand Search), function optimization (Expand Search), codon optimization (Expand Search)
arm optimization » art optimization (Expand Search), swarm optimization (Expand Search), from optimization (Expand Search)
based action » based motion (Expand Search), based active (Expand Search), based fusion (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
based arm » based care (Expand Search), based ap (Expand Search), based ai (Expand Search)
action optimization » reaction optimization (Expand Search), function optimization (Expand Search), codon optimization (Expand Search)
arm optimization » art optimization (Expand Search), swarm optimization (Expand Search), from optimization (Expand Search)
based action » based motion (Expand Search), based active (Expand Search), based fusion (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
based arm » based care (Expand Search), based ap (Expand Search), based ai (Expand Search)
-
1
Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level
Published 2021“…We fill the gap by developing an iterative matching algorithm for the three-group setting. Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”
-
2
-
3
-
4
Block diagram of 2-DOF PIDA controller.
Published 2025“…The controller structure allows independent tuning of set-point tracking and disturbance rejection by introducing separate feedforward paths in the proportional and derivative channels while maintaining integral and acceleration actions on the error signal. To optimize the controller parameters, the recently developed greater cane rat algorithm (GCRA) is employed for the first time in this context. …”
-
5
Zoomed view of Fig 7.
Published 2025“…The controller structure allows independent tuning of set-point tracking and disturbance rejection by introducing separate feedforward paths in the proportional and derivative channels while maintaining integral and acceleration actions on the error signal. To optimize the controller parameters, the recently developed greater cane rat algorithm (GCRA) is employed for the first time in this context. …”
-
6
Zoomed view of Fig 10.
Published 2025“…The controller structure allows independent tuning of set-point tracking and disturbance rejection by introducing separate feedforward paths in the proportional and derivative channels while maintaining integral and acceleration actions on the error signal. To optimize the controller parameters, the recently developed greater cane rat algorithm (GCRA) is employed for the first time in this context. …”
-
7
Analysis and design of algorithms for the manufacturing process of integrated circuits
Published 2023“…The (approximate) solution proposals of state-of-the-art methods include rule-based approaches, genetic algorithms, and reinforcement learning. …”
-
8
DataSheet1_Computational design of custom therapeutic cells to correct failing human cardiomyocytes.pdf
Published 2023“…</p><p>Methods: Candidate custom cells were simulated with a combination of ion channels from non-excitable cells and healthy human cardiomyocytes (hCMs). Using a genetic algorithm-based optimization approach, candidate cells were accepted if a root mean square error (RMSE) of less than 50% relative to healthy hCM was achieved for both action potential and calcium transient waveforms for the cell-treated HF cardiomyocyte, normalized to the untreated HF cardiomyocyte.…”
-
9
DataSheet1_Computational design of custom therapeutic cells to correct failing human cardiomyocytes.pdf
Published 2023“…</p><p>Methods: Candidate custom cells were simulated with a combination of ion channels from non-excitable cells and healthy human cardiomyocytes (hCMs). Using a genetic algorithm-based optimization approach, candidate cells were accepted if a root mean square error (RMSE) of less than 50% relative to healthy hCM was achieved for both action potential and calcium transient waveforms for the cell-treated HF cardiomyocyte, normalized to the untreated HF cardiomyocyte.…”
-
10
Data_Sheet_1_How Morphological Computation Shapes Integrated Information in Embodied Agents.PDF
Published 2021“…There, we calculate the optimal policy for goal-directed behavior based on the “planning as inference” method, in which the information-geometric em-algorithm is used to optimize the likelihood of the goal. …”