Lihua Feng

dblp:81/6131 · DBLP profile ↗
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11ranked-venue papers
4as first author
3since 2021 · last 2026
—ORCID · conflict

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Theory of computation · 7 · 1 first-author · 3 since 2021Artificial intelligence and machine learning · 3 · 3 first-authorDatabases, data management, data science and information retrieval · 1
YearPublicationVenuePosition
2026 Maximal non-empty cross s -union families
abstract
Two families of sets F and G are said to be cross s -union if for any F ∈ F and G ∈ G , | F ∪ G | ≤ s . In 2021, Frankl and Wong proved that if F , G ⊆ 2 [ n ] are non-empty cross s -union, then | F | + | G | ≤ ∑ i = 0 s n i + 1 . Moreover, for s < n − 1 , equality holds if and only if F , G = { 0̸ } , { G ⊆ [ n ] : | G | ≤ s } . In this paper, we give a new method to prove this result. Our method also allows us to establish a vector space version and a hereditary family extension. As a byproduct, we revisit the vector space version of the Katona s -union theorem due to Frankl and Tokushige, and characterize the extremal families for the case s = n − 1 .
Yongjiang Wu, Zhiyi Liu, Lihua Feng, Tingzeng Wu
Discret. Appl. Math.4
2025 Alternating L-functions of finite digraphs
Yongjiang Wu, Lihua Feng
Discret. Appl. Math.2
2022 Optimal identifying codes of two families of Cayley graphs
Min Feng 0004, Xuanlong Ma, Lihua Feng
Discret. Appl. Math.3
2020 On the zeros of the partial Hosoya polynomial of graphs
Modjtaba Ghorbani, Matthias Dehmer, Shujuan Cao, Lihua Feng, Frank Emmert-Streib
Inf. Sci.4
2019 A sufficient Q-spectral condition for a graph to be β-deficient involving minimum degree
Lihua Feng
Discret. Appl. Math.4
2017 Wiener index, Harary index and graph properties
Lihua Feng
Discret. Appl. Math.1
2017 Further results on the largest matching root of unicyclic graphs
Qiang Guo 0010, Lihua Feng, Ivan Gutman
Discret. Appl. Math.4
2011 Degree distance of unicyclic and bicyclic graphs
Aleksandar Ilic, Dragan Stevanovic, Lihua Feng, Guihai Yu, Peter Dankelmann
Discret. Appl. Math.3
2009 Study on water resource risk using the interior-outer set model
abstract
There is a transition from a fuzzy set to crisp set. Therefore, we can obtain a conservative risk value, a venture risk value and a maximum probability risk value. Under such an alpha level, three risk values can be calculated. As alpha adopts all values throughout the set, it is possible to obtain a series of risk values. Therefore, the fuzzy risk may be a multi-valued risk or set-valued risk. Calculation of the fuzzy expected value of Yiwu city's water resource risk has been performed based on the interior-outer set model. Selection of an alpha value depends on the confidence in different groups of people, while selection of a conservative risk value or venture risk value depends on the risk preference of these people.
Lihua Feng
FUZZ-IEEE1
2009 A New Practical Method on Hydrological Calculation
Lihua Feng, Xingcai Zhang
ISNN (1)1
2009 Classification error of multilayer perceptron neural networks
Lihua Feng, Weihu Hong
Neural Comput. Appl.1