Search · four archives
Search · four archives
15 papers · ranked by Valyu relevance
Yunpeng Ma, Wanting Meng, Ruixue Gu, Xinxin Zhang + 1 more
The Black-winged Kite Algorithm (BKA) is a novel heuristic optimization algorithm proposed in 2024, which has demonstrated superior optimization performance on most CEC benchmark functions and several engineering problems. To further enhance its convergence accuracy and solution quality, this paper proposes a Modified…
Mashar Cenk Gençal, Barış Ata, Mehmet Kurucan, Emre Kılınç
Urban environments impose complex challenges for the navigation of unmanned aerial vehicles (UAVs), including dense obstacles, no-fly zones, energy constraints, and regulatory restrictions. Addressing these challenges requires efficient and robust optimization techniques. This study introduces the Improved Roosters…
Taybe Alabed, Sema Servi, Bolin Liao, Shuai (Steven) Li + 1 more
Clustering is a fundamental unsupervised learning technique used to uncover hidden patterns in unlabeled data. Although metaheuristic algorithms have demonstrated effectiveness in clustering, many suffer from premature convergence and limited population diversity. This study employs the Black-Winged Kite Algorithm…
Ömer Karakoç, Samet Memiş, Bahar Sennaroglu, Rajesh Kumar
This study provides a comprehensive evaluation and classification of 35 soft decision-making (SDM) algorithms based on fuzzy parameterized fuzzy soft matrices (fpfs-matrices). Although fpfs-matrices offer a strong mathematical framework for modeling uncertainty, there has been a lack of large-scale comparisons of their…
Elizabeth J. Horn, Barry Menefee, Anna M. Schotthoefer, George Dempsey + 6 more
Current laboratory testing for Lyme disease (LD) relies on serology. We evaluated the performance of standard two-tiered testing (STTT) and modified two-tiered testing (MTTT) algorithms using samples obtained from well-characterized patients with early LD in the U.S. East Coast and Upper Midwest. Participants with…
Ali Asghari, Mohammadhossein Mohammadi, Heming Jia
Metaheuristic algorithms are widely used to find optimal or near-optimal solutions for complex problems by taking inspiration from natural behaviors and processes. Although many different methods have been developed, a common problem in many of them is maintaining a good balance between exploration and exploitation and…
Ahmed Mehedi Nizam, Zeheng Wang
We introduce a supervised learning method that classifies each test point by selecting the class for which its inclusion causes minimum displacement of the class’s existing n-th central moment. After each such inclusion, the n-th central moment of the corresponding class is updated by some incremental calculations in…
Zhijie Luo, Shaoxin Li, Wufa Long, Rui Chen + 1 more
Digital microfluidic biochips (DMFBs) find extensive applications in biochemical experiments, medical diagnostics, and safety-critical domains, with their reliability dependent on efficient online testing technologies. However, traditional random search algorithms suffer from slow convergence and susceptibility to…
Chao Zhang, Yufei Zhang, Feng Wang, Xiaoxu Su + 3 more
The multi-valued dependency matrix (MVD matrix) is an important testability modeling approach, which can deliver more comprehensive testability information than the traditional dependency matrix (D-matrix). However, existing testability strategy optimization algorithms perform poorly in handling the MVD matrix, and the…
Ahmad Eid, Abdulrahman Alsafrani
Numerous optimization techniques have recently been employed in the literature to enhance various electric power systems. Optimization algorithms help system operators determine the optimal location and capacity of any renewable energy source (RES) connected to a system, enabling them to achieve a specific goal and…
Mohammed Alaa Ala’anzy, Nurdaulet Tolendi, Baizhan Baubek, Abdulmohsen Algarni + 1 more
Sorting can be approached in two main ways: sequentially and in parallel. In sequential sorting, data is processed in a single-threaded manner, which can be slow for large datasets. However, parallel sorting divides the task across multiple processing units, enabling faster results by processing data simultaneously.…
MingXuan Jian, GuoZhen Wu, BangLing Xiao
Metaheuristic optimization algorithms are widely used to tackle complex, high-dimensional, and nonlinear problems by mimicking natural or social behaviors, showing great potential for future development. Among them, the Parrot Optimization (PO) algorithm, inspired by the green-cheeked conure, exhibits strong…
N. Jayalakshmi, K. Sakthivel
To achieve robust and user friendly software, it is crucial to make sure that Graphical User Interfaces (GUI) is of quality and reliable. The paper suggests a new method of Quasi-Oppositional Genetic Sparrow Search Algorithm (OOGSSA) of generating test cases efficiently in GUI. The ultimate goal is to have…
Ömer Şakar, Mohsen Safari, Marieke Huisman, Anton Wijs
GPU programs are widely used in industry. To obtain the best performance, a typical development process involves the manual or semi-automatic application of optimizations prior to compiling the code. Such optimizations can introduce errors. To avoid the introduction of errors, we can augment GPU programs with (pre- and…
Fan Zhong, Changyu Ni, Bingshun Wang, Julia Robinson
Pooled testing represents a cost-efficient strategy for large-scale respiratory virus screening. However, determining the optimal pool size (OPS) across varying prevalence rates and diagnostic performance metrics remains a critical challenge in respiratory virus surveillance. We evaluated four hierarchical OPS…