Search · four archives
Search · four archives
17 papers · ranked by Valyu relevance
Faisal Siddiq, Yaseer Arafat Durrani, Lalit Chandra Saikia
Low-power consumption has been always a crucial design constraint for an efficient intellectual property based three-dimensional multi-core system that cannot be ignored easily. As the complexity increases due to the number of cores/stacks/ layers in 3D digital systems, the challenges to handle power can be more…
Marco Pepe, Mohsen Hesami, Finlay Small, Andrew Maxwell Phineas Jones
'Andrew Maxwell Phineas Jones'] Micropropagation techniques offer opportunity to proliferate, maintain, and study dynamic plant responses in highly controlled environments without confounding external influences, forming the basis for many biotechnological applications. With medicinal and recreational interests for…
Xiaojie Tang, Pengju Qu, Zhengyang He, Chengfen Jia + 2 more
Biogeography-based optimization (BBO) is a population-based metaheuristic algorithm inspired by species migration among habitats. However, the original BBO often suffers from premature convergence and insufficient population diversity when solving complex optimization problems. To address these limitations, this paper…
Min Zhu, Zihao Xu, Zhaoyu Zang, Xueping Dong + 3 more
'Junjie Fu' 'Jialing Zhou'] Aiming at the problems of nonlinearity and inaccuracy in the model of the pneumatic control valve position in the industrial control process, a valve position control method based on a fractional-order PID controller is proposed. The working principle of the pneumatic control valve is…
Murteda Unverdi, Ramin Kazemi, Yahya Kaya, Naz Mardani + 2 more
'Seyedali Mirjalili'] Roller compacted concrete (RCC) has gained prominence in the construction industry due to its durability, cost-effectiveness, and environmental benefits, particularly with the incorporation of high-volume fly ash (HVFA). However, traditional experimental approaches to evaluating RCC’s mechanical…
Licheng Jiao, Jiaxuan Zhao, Chao Wang, Xu Liu + 6 more
'Lingling Li' 'Ronghua Shang' 'Yangyang Li' 'Wenping Ma' 'Shuyuan Yang'] Nature, with its numerous surprising rules, serves as a rich source of creativity for the development of artificial intelligence, inspiring researchers to create several nature-inspired intelligent computing paradigms based on natural mechanisms.…
Vanita Garg, Kusum Deep, Khalid A. Alnowibet, Ali Wagdy Mohamed + 2 more
'Mohammad Shokouhifar' 'Frank Werner'] Abstract: In this paper, an ensemble metaheuristic algorithm (denoted as LX-BBSCA) is introduced. It combines the strengths of Laplacian Biogeography-Based Optimization (LX-BBO) and the Sine Cosine Algorithm (SCA) to address structural engineering design optimization problems. Our…
M.Z. Naser, Abdallah Naser
Problems Authors: ['M.Z. Naser' 'Abdallah Naser'] This paper presents the Firefighter Optimization (FFO) algorithm as a new hybrid metaheuristic for optimization problems. This algorithm stems inspiration from the collaborative strategies often deployed by firefighters in firefighting activities. To evaluate the…
Huan Zhou, Hao-Yu Cheng, Zheng-Lei Wei, Xin Zhao + 2 more
'Lei Xie'] The butterfly optimization algorithm (BOA) is a swarm-based metaheuristic algorithm inspired by the foraging behaviour and information sharing of butterflies. BOA has been applied to various fields of optimization problems due to its performance. However, BOA also suffers from drawbacks such as diminished…
Subhrangshu Adhikary
The challenge of finding a global optimum in a solution search space with limited resources and higher accuracy has given rise to several optimization algorithms. Generally, the gradient-based optimizers converge to the global solution very accurately, but they often require a large number of iterations to find the…
Hisham A. Shehadeh, Mohd Yamani Idna Idris, Iqbal H. Jebril
In this paper, a novel bio-inspired optimization algorithm is proposed, called "Bombardier Beetle Optimizer (BBO)". This type of species is very intelligent, which has an ability to defense and escape from predators. The principles of the former one is inspired by the defense mechanism of Bombardier Beetle against the…
Marco Gabrielli, Frederik Hammes
Biofilm microbial communities are characterized by spatial heterogeneity arising in response to environmental characteristics and the metabolic requirements of their inhabitants, which create biogeographical patterns at both large and small scales. While the impact of small-scale biogeography on several emergent…
Charlotte Merzbacher, Oisin Mac Aodha, Diego A. Oyarzún
Recent advances in synthetic biology have enabled the construction of molecular circuits that operate across multiple scales of cellular organization, such as gene regulation, signalling pathways and cellular metabolism. Computational optimization can effectively aid the design process, but current methods are…
Amaras Nazarians, Sachin Kumar
—Hyperparameter tuning is a critical yet computationally expensive step in training neural networks, particularly when the search space is high dimensional and nonconvex. Metaheuristic optimization algorithms are often used for this purpose due to their derivative free nature and robustness against local optima. In…
Andre KY Low, Flore Mekki-Berrada, Aleksandr Ostudin, Jiaxun Xie + 7 more
The development of automated high-throughput experimental platforms has enabled fast sampling of high-dimensional decision spaces. To reach target properties efficiently, these platforms are increasingly paired with intelligent experimental design. When solving optimization problems, Bayesian-based optimizers are often…
Aneta Neumann, Denis Antipov, Frank Neumann
Computing diverse sets of high quality solutions for a given optimization problem has become an important topic in recent years. In this paper, we introduce a coevolutionary Pareto Diversity Optimization approach which builds on the success of reformulating a constrained single-objective optimization problem as a…
Prasad U. Bandodkar, Razeen R. Shaikh, Gregory T. Reeves
Model development is essential to gain a mathematical understanding of the underlying phenomena in systems biology. In most models, it is typically hard to estimate the values of the biophysical/phenomenological parameters that characterize the model. The parameters are estimated by minimizing a function that reduces a…