Artificial neural networks have proven to be effective in a wide range of fields, providing solutions to various problems. Training artificial neural networks using evolutionary algorithms is known as neuroevolution. The idea of finding not only the...
Snake robots constitute bio-inspired solutions that have been studied due to their ability to move in challenging environments where other types of robots, such as wheeled or legged robots, usually fail. In this paper, we consider both land-based and...
Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks...
In the brick manufacturing industry, there is a growing concern among researchers to find solutions to reduce energy consumption. An industrial process for obtaining bricks was approached, with the manufacturing mix modified via the introduction of s...
Neural networks have demonstrated their usefulness for solving complex regression problems in circumstances where alternative methods do not provide satisfactory results. Finding a good neural network model is a time-consuming task that involves sear...
Designing effective drug therapies requires balancing competing objectives, such as therapeutic efficacy, safety, and cost efficiency—a task that poses significant challenges for conventional optimization methods. To address this, we propose th...
Biological muscles generate tension from the combined contribution of the passive elastic recoil and the actively controlled contractile mechanisms. Understanding and replicating these passive and active tensions is necessary and beneficial for desig...
Human bone is composed of organic and inorganic composite materials, contributing to its unique strength and flexibility. Hydroxyapatite (HAP) has been extensively studied for bone regeneration, due to its excellent bioactivity and osteoconductivity,...
The battle of currents between AC and DC reignited as a result of the development in the field of power electronics. The efficiency of DC distribution systems is highly dependent on the efficiency of distribution converter, which calls for optimized...
Dynamic systems which underlie controlled systems are expected to increase in complexity as robots, devices, and connected networks become more intelligent. While classical stable systems converge to a stable point (a sink), another type of stability...
In recent years, new metaheuristic algorithms have been developed taking as reference the inspiration on biological and natural phenomena. This nature-inspired approach for algorithm development has been widely used by many researchers in solving opt...
Biological behaviors have inspired the development of numerous evolutionary optimization algorithms [...]
This paper introduces the improvements in natural-frequency-based SHM by applying bio-inspired optimization methods and a vision-based monitoring system for effective damage detection. This paper proposes a natural frequency extraction method using a...
Sustainable energy development consists of design, planning, and control optimization problems that are typically complex and computationally challenging for traditional optimization approaches. However, with developments in artificial intelligence,...
The search for powerful optimizers has led to the development of a multitude of metaheuristic algorithms inspired from all areas. This work focuses on the animal kingdom as a source of inspiration and performs an extensive, yet not exhaustive, review...
Advancements in electronics and software have enabled the rapid development of unmanned aerial vehicles (UAVs) and UAV-assisted applications. Although the mobility of UAVs allows for flexible deployment of networks, it introduces challenges regarding...
To simultaneously improve mass transfer and minimize pressure drop in proton exchange membrane fuel cells (PEMFCs), this study proposes a novel bionic flow field inspired by the streamlined abdominal structure of the peregrine falcon. A three-dimensi...
Jumping mechanisms constitute an important means of resolution in applications such as crossing uneven terrain and space exploration. However, the traditional design mainly uses engineering design thinking, but seldom studies the structural character...
Biomimicry is redefining the design, architecture, and construction industries by transforming biological principles into innovative solutions that optimize structural, energy, and environmental performance. This study identifies the organisms and na...
Spiking Neural Networks (SNNs), with their event-driven and energy-efficient characteristics, have shown great promise in processing data from neuromorphic sensors. However, the sparse and non-stationary nature of event-based data poses significant c...
Optimizing water distribution systems is an essential part of water resources allocation planning. It leads to challenging combinatorial optimization problems, for which meta-heuristics have been applied, notably genetic algorithms and ant colony opt...
In addition to water repellency, superhydrophobic leaves of plants such as Salvinia molesta adsorb oil and separate it from water surfaces. This phenomenon has been the inspiration for a new method of oil–water separation, the bionic oil adsorb...
This survey delves into the Firebug Swarm Optimization (FSO) algorithm, an advanced global optimization algorithm that plays a pivotal role in modern swarm intelligence optimization techniques. It explores the core principles of the FSO algorithm and...
Inspired by the gender transition behavior seen in hawkfish, this paper introduces the HawkFish optimization algorithm, a nature-inspired optimization technique modeled on the unique gender transition behavior of hawkfish. By leveraging this biologic...
Studying the interactions between biological organisms and their environment provides engineers with valuable insights for developing complex mechanical systems and fostering the creation of novel technological innovations. In this study, we introduc...
Starting from Ioffe’s description of a thermoelectric converter, we recover the optimal working points of conversion: the point of maximum efficiency and the one of maximal power. Inspired by biological converters’ optimization, we comput...
The frog-inspired jumping robot is an interesting topic in the field of biomechanics and bionics. However, due to the frog’s explosive movement and large range of joint motion, it is very difficult to make their structure completely bionic. To...
MycelialNet is a novel deep neural network (DNN) architecture inspired by natural mycelial networks. Mycelia, the vegetative part of fungi, form extensive underground networks that, in a very efficient way, connect biological entities, transport nutr...
The widespread application of unmanned vehicles in logistics distribution and special transportation has made improving trajectory tracking accuracy and dynamic adaptability critical for operational efficiency. This article proposes a biologically in...
(1) Background: An iterative learning control (ILC) strategy was developed for a “Muscle First” Motor-Assisted Hybrid Neuroprosthesis (MAHNP). The MAHNP combines a backdrivable exoskeletal brace with neural stimulation technology to enabl...
The literature shows that translating the thermal adaptation mechanisms of biological organisms to building design solutions can improve energy performance. In the context of bio-inspired thermoregulation several worthwhile attempts have been made to...
Credit risk assessment plays a critical role in financial risk management, focusing on predicting borrower default to minimize losses and ensure compliance. This study systematically reviews 23 empirical articles published between 2019 and 2023, high...
Biological systems, ranging from ant colonies to neural ecosystems, exhibit remarkable self-organizing intelligence. Inspired by these phenomena, this study investigates how bio-inspired computing principles can bridge game-theoretic rationality and...
In this paper, the artificial bee colony (ABC) algorithm is hybridized with the genetic algorithm (GA) for a model parameter identification problem. When dealing with real-world and large-scale problems, it becomes evident that concentrating on a sol...
Much of biology-inspired computer science is based on the Central Dogma, as implemented with genetic algorithms or evolutionary computation. That 60-year-old biological principle based on the genome, transcriptome and proteasome is becoming overshado...
This research tackles the critical challenge of achieving precise and efficient feature selection in machine learning-based classification, particularly for smart agriculture, where existing methods often fail to balance exploration and exploitation...
Inspired by biological systems, swarm intelligence algorithms are widely used to solve multimodal optimization problems. In this study, we consider the hybridization problem of an algorithm based on the collective behavior of fish schools. The algori...
This paper introduces a novel bio-inspired metaheuristic algorithm, named the sharpbelly fish optimizer (SFO), inspired by the collective ecological behaviors of the sharpbelly fish. The algorithm integrates four biologically motivated strategies&mda...
Particle swarm optimization (PSO) is a widely used bio-inspired optimization algorithm, yet maintaining an effective balance between exploration and exploitation remains challenging. Most existing PSO variants rely on static or predefined regulation...
Global optimization problems, prevalent across scientific and engineering disciplines, necessitate efficient algorithms for navigating complex, high-dimensional search spaces. Drawing inspiration from the resilient and adaptive growth strategies of m...
The Sporulation-Inspired Optimization Algorithm (SIOA) is an innovative metaheuristic optimization method inspired by the biological mechanisms of microbial sporulation and dispersal. SIOA operates on a dynamic population of solutions (“microor...
Traditional talent identification systems often rely on static assessments and overlook the dynamic nature of long-term development. To address this limitation, this study proposes a biomimetic predictive framework inspired by crayfish behavioral eco...
Biomimetic design, derived from the study of biological systems, has emerged as a pivotal methodology in contemporary art and design. By systematically integrating the morphological traits, structural principles, and functional mechanisms of living o...
Portfolio optimization is fundamental to modern finance, enabling investors to construct allocations that balance risk and return while satisfying practical constraints. When transaction costs and cardinality limits are incorporated, the problem beco...
The concept of privileged structure has been used as a fruitful approach for the discovery of novel biologically active molecules. A privileged structure is defined as a semi-rigid scaffold able to display substituents in multiple spatial directions...
Despite the rapid advances in autonomous guidance and navigation techniques for unmanned aerial vehicle (UAV) systems, there are still many challenges in finding an optimal path planning algorithm that allows outlining a collision-free navigation rou...
Contemporary neural and generative architectures are deficient in self-preservation mechanisms and sustainable stability. In uncertain or noisy situations, they frequently demonstrate oscillatory learning, overconfidence, and structural deterioration...
Porous tubular structures are of significant interest in engineering due to their exceptional potential for lightweight design, energy absorption, and multifunctional integration. Inspired by the unique net architecture of natural luffa sponges, this...
The present research work introduces a novel mixture optimization methodology for biodiesel fuels using an Evolutionary Computation method inspired by biological evolution. Specifically, the optimal biodiesel composition is deduced from the applicati...
The performance of metaheuristic algorithms in solving high-dimensional, non-convex optimization problems is intricately linked to the balance between global exploration and local exploitation. Inspired by biomimetic principles of swarm intelligence,...
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