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.…”

Changes in Punishment Function. by Huiyue Xu (12022388)

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)

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Variations of loss functions versus epoch number. by Xueliang Guo (4797057)

Federated averaging algorithm pseudocode. by Hadi Mohammadian KhalafAnsar (22783784)

The experiment result comparison of algorithms. by Siyu Li (404947)

“…We develop a hybrid heuristic algorithm based on a greedy strategy to obtain the levels of hubs, customer allocation and cargo routing. …”

Linear-Scaling Local Natural Orbital CCSD(T) Approach for Open-Shell Systems: Algorithms, Benchmarks, and Large-Scale Applications by P. Bernát Szabó (10526316)

“…This enables the accurate modeling of large systems with complex electronic structures, as illustrated on open-shell organic radicals and transition-metal complexes of up to 179 atoms as well as on challenging biochemical systems, including up to 601 atoms and 11,000 basis functions. While the protein models involve difficulties for local approximations, such as the spin states of a bounded iron ion or an extremely delocalized singly occupied orbital, the corresponding single-node LNO-CCSD­(T) computations were feasible in a matter of days with 10s to 100 GB of memory use. …”

Faster Exact Exchange for Solids via occ-RI-K: Application to Combinatorially Optimized Range-Separated Hybrid Functionals for Simple Solids with Pseudopotentials Near the Basis Se... by Joonho Lee (1351974)

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Absorption Intensities of Organic Molecules from Electronic Structure Calculations versus Experiments: the Effect of Solvation, Method, Basis Set, and Transition Moment Gauge by Jorge C. Garcia-Alvarez (11934119)

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Comparison of algorithms in two cases. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Flow of the NSGA-II algorithm. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Flowchart of whale flock optimization algorithm. by Rongxin Gong (18864603)

“…<i>camphora</i> growth was established using the multiple linear regression (MLR), partial least squares (PLS), support vector regression (SVR), random forest (RF), radial basis function neural network (RBFNN), back propagation neural network (BPNN), and whale optimization algorithm (WOA)-optimized BPNN models. …”

Non-Iterative Linear Maximization Algorithm by Gerardo L. Febres (4455913)

“…Febres for the theoretical basis of this algorithm.</div>…”

The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers. by Solomon Shiferaw Beyene (9143178)

HIL test results of curved road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. by Honglei Pang (22693724)

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Simulation Results Plot of the SBW System Response: (a) Step response curve of the SBW system; (b) Sine response curve of the SBW system; (c) Steady state error curve of the SBW sy... by Honglei Pang (22693724)

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Simulation Results Plot of the EMB System Response: (a) Step response curve of the EMB system; (b) Sine response curve of the EMB system; (c) Steady state error curve of the EMB sy... by Honglei Pang (22693724)

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HIL test results of low-adhesion road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. by Honglei Pang (22693724)

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HIL test results of split-μ road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. by Honglei Pang (22693724)

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Analytic Gradients for Density Fitting MP2 Using Natural Auxiliary Functions by Klára Petrov (19251734)

“…The natural auxiliary function (NAF) approach is an approximation to decrease the size of the auxiliary basis set required for quantum chemical calculations utilizing the density fitting technique. …”