Yifan He

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Verified

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• Doctor of Philosophy
• Assistant Professor at Zhejiang University of Finance and Economics

A characteristic of human learning is the ability to obtain knowledge from tasks solved in the past and apply the obtained knowledge when solving tasks in the future. The learning behavior consecutively happens when a human solves endless and distinct tasks during his/her lifetime. This learning ability allows humans to solve more complex tasks. Ev...

We introduce Knowledge-Driven Program Synthesis (KDPS) as a variant of the program synthesis task that requires the agent to solve a sequence of program synthesis problems. In KDPS, the agent should use knowledge from the earlier problems to solve the later ones. We propose a novel method based on PushGP to solve the KDPS problem, which takes subpr...

We introduce Knowledge-Driven Program Synthesis (KDPS) as a variant of the program synthesis task that requires the agent to solve a sequence of program synthesis problems. In KDPS, the agent should use knowledge from the earlier problems to solve the later ones. We propose a novel method based on PushGP to solve the KDPS problem, which takes subpr...

Assisted seismic history matching (ASHM) is an optimisation problem that incorporates 4D seismic data as a constraint upon a reservoir simulation update. The observed and simulated three-dimensional seismic data is typically reduced to a Cartesian map representation and the misfit between the two is calculated using the mean squared error (MSE). Th...

Seismic History Matching (SHM) is a key problem in the geosciences community, requiring optimal parameters of a subsurface model that match the observed data from multiple in-situ measurements. Therefore, the SHM problems are usually solved with Multi-Objective Evolutionary Algorithms (MOEAs). This group of algorithms optimize multiple objectives s...

Cuckoo Search (CS) is a simple yet efficient swarm intelligence algorithm based on Lévy Flight. However, its performance can depend heavily on the parameter settings. Though many studies have designed control strategies for scaling factor \(\alpha \), few have considered the adaption of the stability parameter \(\beta \) (of Lévy Flight). In this p...

Portfolio optimization is a financial task which requires the allocation of capital on a set of financial assets to achieve a better trade-off between return and risk. To solve this problem, recent studies applied multi-objective evolutionary algorithms (MOEAs) for its natural bi-objective structure. This paper presents a method injecting a distrib...

Portfolio optimization is a financial task which requires the allocation of capital on a set of financial assets to achieve a better trade-off between return and risk. To solve this problem, recent studies applied multi-objective evolutionary algorithms (MOEAs) for its natural bi-objective structure. This paper presents a method injecting a distrib...

To date, a wide variety of applications are developed and available in iTunes App Store, Google Play and Windows App Market. However, the visually impaired are still unable to enjoy most of them because of the non-optimized design of these applications for them. Though some mobile operating systems provide auditory assistive functions, slow and ted...

In neoclassical economics, Rational Choice Theory states that individuals always make prudent and rational decisions provided with the greatest benefits. In Ultimatum Game, the proposer (Player I) proposes how to split a sum of money. The responder (Player II) decides to accept or reject the proposal. If the responder accepts, the sum is splitted a...