Demonstration of the combinatorial Hill functions (A and B), and the regulation function (C and D) under the regulation of an activator and a repressor. by Ruihao Li (2908991)

Logarithmic mean convergence curves of different algorithms. by Wei Liu (20030)

Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic by NELSON L. DIAS (8078003)

“…These implementations need to utilize high-precision arithmetic, and are programmed in the Python programming language. A thorough comparison with existing R functions allows the identification of cases when the latter fail, and provide further guidance to their use.…”

Phosphorylation-specific motifs identified by the Motif-X algorithm. by Xiaoxiao Qin (9247765)

PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

Subjects:

Performance of the smooth-index algorithm for matrices with different densities. by Alexander Borst (32619)

“…B</b> Performance of the algorithm as a function of the number of neurons. …”

Performance of PCA and Joint Autoencoder (JAE) denoising algorithms. by Ege Altan (11768156)

Line chart plotted using the k-value selection algorithm: (A) system 1; (B) system 2; (C) system 3. by Jingnan Yan (20727331)

Where to Handle an Exception? Recommending Exception Handling Locations from a Global Perspective by Xiangyang Jia (10026932)

CPU usage of benchmark function: (a) CPU Usage during the Execution of Benchmark Functions F21-F30, (b) CPU Usage during the Execution of Benchmark Functions F31-F40 and (c) CPU Us... by Ruyi Dong (9038174)

Iteration curve of benchmark function: (a) Convergence curves of the average best fitness for functions F21-F30, (b) Convergence curves of the average best fitness for functions F3... by Ruyi Dong (9038174)

Histogram showing the distribution of different model parameters over selected individuals in the Genetic Algorithm. by Claudio D. T. Barros (10885464)

“…<p>We selected the 37 best individuals from the full Genetic Algorithm execution, following the criterion of the cost function being less than or equal to 0.069. …”

Brief sketch of the quasi-attraction/alignment algorithm. by Takayuki Niizato (162226)

“…The focal agent selects its next direction randomly based on . (D) A brief sketch of the avoidance algorithm. Upper: Each direction is extended to the repulsion area = {<b><i>r</i></b>||<b><i>r</i></b>| = <i>R</i>}, where is the minimal sphere cap that covers all points on . …”

Variations in the effectiveness and cost of the eight Ebola screening algorithms as a function of the prevalence of Ebola virus disease in the suspected population. by Antoine Oloma Tshomba (14271425)

Workflow of the mycelium characterization algorithm. by Guillermo Vidal-Diez de Ulzurrun (7609925)

Algorithm for generating virtual patients. by Adrianne L. Jenner (11133854)

“…<b>3)</b> A simulated annealing algorithm is then used to determine a parameter set that optimises the objective function <i>J</i>(<i>p</i>) (<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1009753#ppat.1009753.e059" target="_blank">Eq 17</a>). …”

Genetic Algorithm parameter search. by Elishai Ezra-Tsur (11888717)

“…<p><b>a.</b> Initiation of the genetic algorithm population with 100 randomly selected individuals, each with eight parameters (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1009754#sec010" target="_blank">Methods</a>). …”

Schematic view of the overall algorithm. by Betty Wutzl (6945248)

Comparison of different optimization algorithms. by Hang Zhao (143592)

Success maps of the four algorithms. by Ye Lin (613248)