Parameters <i>p</i> identified by the APLM algorithm. by HaiYan Jiang (4455199)

Subjects:

Objective functions (i.e., RMSEs) and time of optimization for different population sizes of the used algorithms. by Yao Peng (1928524)

“…<p>Objective functions (i.e., RMSEs) and time of optimization for different population sizes of the used algorithms.…”

Standard functions to test. by Kemal Gökhan Nalbant (18858009)

Experiment 1b: Evaluating modularity-based consensus clustering pipelines on the algorithm design datasets as a function of the mixing parameter. by Yasamin Tabatabaee (18095491)

Flowchart of the general algorithm for one trial. by Junying Wang (509009)

Algorithm of the brightness scale calibration experiment. by Krzysztof Petelczyc (3954203)

“…<p>In the algorithm, the following variables were used: “I” denotes the current luminous intensity of the reference diode, “inc” denotes the current difference between reference and target diode luminous intensity; “cnt” is the current number of performed trials, while “correct” is a counter of correct answers in cnt trials, both of them are counted separately for every settings of I and inc. …”

Demonstration of algorithm design and operationalization. by Tobias S. Brett (5353364)

“…In panels (f–i), we present a step-by-step outline of how, for any time series data, our fitted algorithm functions as an early warning system. …”

Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... by Ziyan Jin (21021976)

Performance comparison of mainstream algorithms. by Junjie Lu (160350)

Subjects:

Networking Chemicals Flows: Efficiency–Value–Environment Functionalized Symbiosis Algorithms and Application by Yizheng Lyu (17346506)

Networking Chemicals Flows: Efficiency–Value–Environment Functionalized Symbiosis Algorithms and Application by Yizheng Lyu (17346506)

Networking Chemicals Flows: Efficiency–Value–Environment Functionalized Symbiosis Algorithms and Application by Yizheng Lyu (17346506)

Efficient algorithms to discover alterations with complementary functional association in cancer by Rebecca Sarto Basso (6728921)

“…We provide analytic evidence of the effectiveness of UNCOVER in finding high-quality solutions and show experimentally that UNCOVER finds sets of alterations significantly associated with functional targets in a variety of scenarios. In particular, we show that our algorithms find sets which are better than the ones obtained by the state-of-the-art method, even when sets are evaluated using the statistical score employed by the latter. …”

Route for bays29 output by ABSQL algorithm. by Jin Zhang (53297)

“…DSRABSQL builds upon the Q-learning (QL) algorithm. Considering its problems of slow convergence and low accuracy, four strategies within the QL framework are designed first: the weighting function-based reward matrix, the power function-based initial Q-table, a self-adaptive <i>ε-beam</i> search strategy, and a new Q-value update formula. …”

Hyperparameter settings of the algorithm 1. by Jin Xu (31283)

“…Subsequently, a state space is selected, and a dense reward function is designed, considering the multivariable characteristics of the recirculating cooling water system. …”

Circulatory system-based optimization algorithm with dynamic penalty function for optimum design of large-scale water distribution networks by Veli Batmaz (20800175)

“…The impact of a dynamic penalty function tailored to pressure constraints on the optimal design is also investigated. …”

Reward function related parameters. by Honglei Pang (22693724)

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Average quality scores of the models of the analysis set as a function of the <i>w</i>_<i>SP</i> with which the DOPE potential has been included in the objective function... by Giacomo Janson (8138517)

Running memory of the algorithms. by Yanju Zhang (437336)

Subjects:

Genetic algorithms can be applied to higher-dimensional design problems. by Lu Hong (399882)

Subjects: