753 Results Found

Text clustering is one of the efficient unsupervised learning techniques used to partition a huge number of text documents into a subset of clusters. In which, each cluster contains similar documents and the clusters contain dissimilar text documents...

Although it is a well-researched topic, the complexity, time for process stabilization, and economic factors related to anaerobic digestion call for simulation of the process offline with the help of computer models. Nature-inspired techniques are a...

This paper uses a nature-inspired optimization algorithm to discuss the automatic selection of control structure parameters. The commonly used quality indicators are presented and analyzed for the optimization process of the control system. Moreover,...

In recent years, optimization problems have been intriguing in the field of computation and engineering due to various conflicting objectives. The complexity of the optimization problem also dramatically increases with respect to a complex search spa...

In numerous scientific disciplines and practical applications, addressing optimization challenges is a common imperative. Nature-inspired optimization algorithms represent a highly valuable and pragmatic approach to tackling these complexities. This...

Over previous decades, many nature-inspired optimization algorithms (NIOAs) have been proposed and applied due to their importance and significance. Some survey studies have also been made to investigate NIOAs and their variants and applications. How...

This paper reviews a majority of the nature-inspired algorithms, including heuristic and meta-heuristic bio-inspired and non-bio-inspired algorithms, focusing on their source of inspiration and studying their potential applications in drones. About 3...

The activated sludge process (ASP) is the most widely used biological wastewater treatment system. Advances in research have led to the adoption of Artificial Intelligence (AI), in particular, Nature-Inspired Algorithm (NIA) techniques such as Geneti...

One of the most challenging problems that are still open in the field of materials science is the 3D reconstruction of porous media using information from a single 2D thin image of the original material. Such a reconstruction is only feasible subject...

This paper introduces a novel nature-inspired optimization algorithm called the Grizzly Bear Fat Increase Optimizer (GBFIO). The GBFIO algorithm mimics the natural behavior of grizzly bears as they accumulate body fat in preparation for winter, drawi...

Nature-inspired metaheuristics have proven effective for addressing complex structural optimization challenges where traditional deterministic or gradient-based methods often fall short. This study investigates the feasibility and benefits of embeddi...

Dew point temperature (DPT) is known to fluctuate in space and time regardless of the climatic zone considered. The accurate estimation of the DPT is highly significant for various applications of hydro and agro–climatological researches. The current...

The problem of the shape optimization of tubular-type plug-flow chemical reactors equipped with a fluid flow-based cooling system is considered in this work. The hydraulic radius R_h(z) = 2A(z)/P(z) and an equivalent surface area-based radius R_s = P(z...

In this paper, a hybrid nature-inspired metaheuristic algorithm based on the Genetic Algorithm and the African Buffalo Optimization is proposed. The hybrid approach adaptively switches between the Genetic Algorithm and the African Buffalo Optimizatio...

Speckle noise is a pervasive problem in medical imaging, and conventional methods for despeckling often lead to loss of edge information due to smoothing. To address this issue, we propose a novel approach that combines a nature-inspired minibatch wa...

Optimization is an important and fundamental challenge to solve optimization problems in different scientific disciplines. In this paper, a new stochastic nature-inspired optimization algorithm called Pelican Optimization Algorithm (POA) is introduce...

Accurate prediction of building energy loads is essential for smart buildings and sustainable energy management. While machine learning (ML) approaches outperform traditional statistical models at capturing nonlinear relationships, most studies prima...

The increasing number, frequency, and sophistication of phishing website-based attacks necessitate the development of robust solutions for detecting phishing websites to enhance the overall security of cyberspace. Drawing inspiration from natural pro...

In electrical engineering problems, bio- and nature-inspired optimization techniques are valuable ways to minimize or maximize an objective function. We use the root tree algorithm (RTO), inspired by the random movement of roots, to search for the gl...

This paper presents Rain-Cloud Condensation Optimizer (RCCO), a nature-inspired metaheuristic that maps cloud microphysics to population-based search. Candidate solutions (“droplets”) evolve under a dual-attractor dynamic toward both a gl...

Humanity has consumed large amounts of energy in recent decades. Energy requirements increase continuously, and fossil fuel overuse pollutes the environment extremely. The researchers turned their attention to alternative solutions, such as renewable...

Warehousing is one of the most important activities in the supply chain, enabling competitive advantage. Effective management of warehousing processes is, therefore, crucial for achieving minimal costs, maximum efficiency, and overall customer satisf...

The quality of machine learning models can suffer when inappropriate data is used, which is especially prevalent in high-dimensional and imbalanced data sets. Data preparation and preprocessing can mitigate some problems and can thus result in better...

The new paradigm of nature-inspired cybersecurity can establish a robust defense by utilizing well-established nature-inspired computing algorithms to analyze networks and act quickly. The existing research focuses primarily on the efficient selectio...

This work presents a rat optimization algorithm (ROA), which simulates the social behavior of rats and is a new nature-inspired optimization technique. The ROA consists of three operators that simulate rats searching for prey, chasing and fighting pr...

Microgrids have been popularized in the past decade because of their ability to add distributed generation into the classic distribution systems. Protection problems are among several other problems that need solutions in order to extract the full ca...

Development of present-day antenna systems is an intricate and multi-step process requiring, among others, meticulous tuning of designable (mainly geometry) parameters. Concerning the latter, the most reliable approach is rigorous numerical optimizat...

This article introduces a novel nature-inspired algorithm called the Plum Tree Algorithm (PTA), which has the biology of the plum trees as its main source of inspiration. The PTA was tested and validated using 24 benchmark objective functions, and it...

This paper introduces the Enhanced Team-Oriented Swarm Optimization (ETOSO) algorithm, a novel refinement of the Team-Oriented Swarm Optimization (TOSO) algorithm aimed at addressing the stagnation problem commonly encountered in nature-inspired opti...

Nature-inspired algorithms allow us to solve many problems related to the search for optimal solutions. One such issue is the problem of searching for optimal routes. In this paper, ant colony optimization is used to search for optimal tram routes. A...

This contribution investigates the performance of nature-inspired multi-objective optimization algorithms to reduce the makespan and oven idle time of bakery manufacturing using a hybrid no-wait flow shop scheduling model. As an example, the producti...

In recent years, several high-performance nature-inspired metaheuristic algorithms have been proposed. It is important to study and compare the convergence, computational burden and statistical significance of these metaheuristics to aid future devel...

Blade design of the horizontal axis wind turbine (HAWT) is an important parameter that determines the reliability and efficiency of a wind turbine. It is important to optimize the capture of the energy in the wind that can be correlated to the power...

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...

Cyber-physical systems (CPSes) are rapidly evolving in critical infrastructure (CI) domains such as smart grid, healthcare, the military, and telecommunication. These systems are continually threatened by malicious software (malware) attacks by adver...

There is a constant push towards increasing use of renewable energy-based distributed generators around the globe. While they provide a clean and sustainable source of energy, they employ technologies that are unknown to traditional power systems. Th...

In this study, a hybrid sensor-based electronic nose circuit was developed using eight metal-oxide semiconductors and 14 quartz crystal microbalance gas sensors. This study included 100 participants: 60 individuals diagnosed with lung cancer, 20 heal...

The growing energy demand around the world has increased the usage of renewable energy sources (RES) such as photovoltaic and wind energies. The combination of traditional power systems and RESs has generated diverse problems due especially to the st...

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...

This research addresses the sensor placement optimization problem (SPOP) in the industrial sector, aiming to enhance operational efficiency and safety through the strategic deployment of sensors. The focus is on optimizing the locations of thermal ca...

In this paper, we propose a novel nature-inspired meta-heuristic algorithm for continuous global optimization, named the phase transition-based optimization algorithm (PTBO). It mimics three completely different kinds of motion characteristics of ele...

Brain storm optimization (BSO) and particle swarm optimization (PSO) are two popular nature-inspired optimization algorithms, with BSO being the more recently developed one. It has been observed that BSO has an advantage over PSO regarding exploratio...

The paper presents the optimization of stacking sequence (the lamination angles in subsequent composite layers) of the composite cylinder in order to simultaneously maximize the values of the first natural frequency $f_1$ and the first buckling force $P_c$...

This paper focuses on the resilience of a nature-inspired class of algorithms. The issues related to resilience fall under a very wide umbrella. The uncertainties that we face in the world require the need of resilient systems in all domains. Softwar...

The seismic design of structures is an emerging practice in earthquake-resistant construction. Therefore, using energy-dissipation devices and optimizing these devices for various purposes are important. Evolutionary computation, nature-inspired, and...

This paper presents the discrete version of the Mycorrhiza Tree Optimization Algorithm (MTOA), using the Lotka–Volterra Discrete Equation System (LVDES) formed by the Predator–Prey, Cooperative and Competitive Models. The Discrete Mycorrh...

The Aquila Optimizer (AO), inspired by the hunting behavior of Aquila birds, is a recent nature-inspired metaheuristic algorithm recognized for its simplicity and low computational cost. However, the conventional AO often suffers from premature conve...

This paper proposes a method for solving the path planning problem for a collaborative robot. The time-optimal, smooth, collision-free B-spline path is obtained by the application of a nature-inspired optimization algorithm. The proposed approach can...

In this paper, a novel heuristic search algorithm called Smart Root Search (SRS) is proposed. SRS employs intelligent foraging behavior of immature, mature and hair roots of plants to explore and exploit the problem search space simultaneously. SRS d...

The present study introduces a novel nature-inspired optimizer called the Pine Cone Optimization algorithm (PCOA) for solving science and engineering problems. PCOA is designed based on the different mechanisms of pine tree reproduction, including po...