Multilevel thresholding is one of the most effective image segmentation methods, due to its efficiency and easy implementation. This study presents a new multilevel thresholding method based on a modified artificial ecosystem-based optimization (AEO)...
Electrification of remote rural areas by adopting renewable energy technologies through the advancement of smart micro-grids is indispensable for the achievement of continuous development goals. Satisfying the electricity demand of consumers while ad...
In this paper, the optimal design of a hybrid energy system (HES), consisting of photovoltaic technology integrated with fuel cells (HPV/FC) and relying on hydrogen storage, is performed to meet the annual demand of a residential complex to find the...
Over the last decade, dual active bridge (DAB) converters have become critical components in high-frequency power conversion systems. Recently, intensive efforts have been directed at optimizing DAB converter design and control. In particular, severa...
Tuberculosis (TB) is is an infectious disease that generally attacks the lungs and causes death for millions of people annually. Chest radiography and deep-learning-based image segmentation techniques can be utilized for TB diagnostics. Convolutional...
Increasing waste generation has become a key challenge around the world due to the dramatic expansion in industrialization and urbanization. This study focuses on providing effective solutions for real-time monitoring garbage collection systems via t...
The most effective use of numerous Combined Heat and Power Units (CHPUs) is a challenging issue that requires strong approaches to handle the Economic Dispatch (ED) with CHPUs. It aims at minimizing the fuel costs by managing the Power-Only Units (PO...
The agricultural industry has the potential to meet the increasing food production requirements and supply nutritious and healthy food products. Since the Internet of Things (IoT) phenomenon has achieved considerable growth in recent years, IoT-based...
The reliable mathematical model construction of dye-sensitized solar cells (DSSCs) using the triple-diode model (TDM) is proposed but it is a challenge due to its complexity. This work implements a novel method incorporating a recent meta-heuristic o...
In this study, the optimum design for an induction motor (IM) was realized by providing details of its geometric design. The IM optimization was carried out using the Artificial Ecosystem-based Optimization (AEO) algorithm, a metaheuristic method. Th...
In this study, an optimization algorithm called chaotic turbulent flow of water-based optimization (CTFWO) algorithm is proposed to find the optimal solution for the optimal reactive power dispatch (ORPD) problem. The ORPD is formulated as a complica...
Nowadays, AC distributed power networks are facing many challenges in guaranteeing and improving the required level of power quality indices in power networks with increasing nonlinear, time-variable and unbalanced loads. Power networks can benefit f...
The proton exchange membrane fuel cell (PEMFC) is a green energy converter that is based on the chemical reaction process. The behavior of this system can change with time due to aging and operating conditions. Knowing the current state of this syste...
This study proposes a hybrid analytical–numerical method for accurately extracting five physically meaningful single-diode-model (SDM) parameters from measured illuminated I–V data. Five experimental data points are randomly selected to c...
Backfilling materials are commonly employed materials in mines for filling mining waste, and the strength of the consolidated backfill formed by the binding material directly influences the stability of the surrounding rock and production safety in m...
The study aimed to address the complex and critical issue of surface water quality monitoring by proposing a diversified approach that incorporates a range of chemical indicators. (1) Background: the purpose of the study was to address the problem of...
Exploring the spatial distribution of land use/cover change (LUCC) and ecosystem carbon storage under future climate change scenarios can provide the scientific basis for optimizing land resource redistribution and formulating policies for sustainabl...
Intelligent oilfield development is experiencing an increasingly deep integration between localized automation and integrated, data-centric ecosystems. To systematically delineate the knowledge structure and technological trajectories within this fie...
Over the years, artificial reefs with diverse forms and functions have become increasingly important in maritime engineering and ecosystem restoration plans, with socio-economic and ecological impacts on marine ecosystems. However, due to the increas...
This study focuses on the intrinsic mechanisms and sustainable value of artificial intelligence (AI)-driven green collaborative innovation in enterprises amid the global green low-carbon transition, revealing new pathways for digital technology-enabl...
Due to their toxicity, Cr(VI) levels are subject to strict legislation and regulations in various industries and environmental contexts. Effective treatment technologies are also being developed to decrease the negative impacts on human health and th...
The gut microbiota is a complex and dynamic ecosystem that plays a fundamental role in human health by regulating immunity, metabolism, and the gut–brain axis. Beyond its critical physiological functions, it has emerged as a rich source of insp...
Hydrological connectivity affects the material cycling and energy transfer of ecosystems and is an important indicator for assessing the function of aquatic ecosystems. Therefore, clarification of hydrologic connectivity and its optimization methods...
Coastal erosion and sediment transport dynamics in Iraq’s shoreline are increasingly affected by extreme climate conditions, including rising sea levels and intensified storms. This study introduces a novel fractional-order sediment transport m...
The study focused on optimizing carbon sequestration in urban artificial wetlands, using the Shanghai Fish and Dishui Lake as case studies. As cities like Shanghai experienced rapid urbanization, natural wetland areas diminished, making artificial we...
Many process-based models for carbon flux predictions have faced a wide range of uncertainty issues. The complex interactions between the atmosphere and the forest ecosystems can lead to uncertainties in the model result. On the other hand, artificia...
The rate of technical innovation, system interconnection, and advanced communications undoubtedly boost distributed energy networks’ efficiency. However, when an additional attack surface is made available, the possibility of an increase in att...
As rivers face growing environmental challenges due to climate change and the construction of artificial structures, it is essential that we improve river ecosystems to maintain their ecological functions and preserve the health of aquatic habitats....
The time-series analysis of multi-temporal satellite data is widely used for vegetation regrowth after a wildfire event. Comparisons between pre- and post-fire conditions are the main method used to monitor ecosystem recovery. In the present study, w...
Tomato (Solanum lycopersicum L.) production faces increasing pressure from resource scarcity and climate change, creating demand for more precise and adaptive management. However, adoption in commercial systems remains limited because many advanced t...
This study performed a comparative analysis of five new meta-heuristic algorithms specifically adopted based on two general classifications; namely, nature-inspired, which includes artificial eco-system optimization (AEO), African vulture optimizatio...
The increasing threat of biological invasion poses significant challenges to global ecosystems, necessitating urgent management measures. This study investigated the potential of biochar derived from invasive plant Chromolaena odorata, produced throu...
The provision and utilization of grassland resources connect grassland ecosystems and pastoral society. Revealing the mechanism behind the forage supply–demand relationship and balancing forage supply and demand is essential in pastoral socio-e...
Rivers play a major role within ecosystems and society, including for domestic, industrial, and agricultural uses, and in power generation. Forecasting of suspended sediment yield (SSY) is critical for design, management, planning, and disaster preve...
A new emergent intelligence approach to the design of smart ecosystems, based on the complexity science principles, is introduced and discussed. The smart ecosystem for resource management is defined as a system of autonomous decision-making multi-ag...
Water quality monitoring remains a critical challenge for achieving Sustainable Development Goal 6, particularly in rural and resource-constrained environments where conventional laboratory-based methods are costly and slow. This study presents the d...
The present study introduces a subtraction-average-based optimization algorithm (SAOA), a unique enhanced evolutionary technique for solving engineering optimization problems. The typical SAOA works by subtracting the average of searcher agents from...
Chlorophyll-a (Chl-a) concentration monitoring is very important for managing water resources and ensuring the stability of marine ecosystems. Due to their high operating efficiency and high prediction accuracy, backpropagation (BP) neural networks a...
Manufacturing as a Service (MaaS) has emerged as a transformative paradigm at the intersection of Industry 4.0 and servitization, enabling flexible, sustainable, and intelligent production through on-demand provisioning of manufacturing resources. By...
Driven by the rapid proliferation of generative artificial intelligence, the computing power industry is undergoing a paradigm shift from traditional linear supply chains toward complex, interdependent innovation ecosystems. This study investigates t...
Background: Artificial intelligence (AI) in urban and multimodal transport has demonstrated strong potential; however, real-world deployment remains constrained by limited governance-ready design, fragmented data ecosystems, and single-objective opti...
The vertical structure of forest ecosystems influences and reflects ecosystem functioning. Terrestrial laser scanning (TLS) enables the rapid acquisition of 3D forest information and subsequent reconstruction of the vertical structure, which provides...
Hydroponics refers to a modern set of agricultural techniques that do not require the use of natural soil for plant germination and development. These types of crops use artificial irrigation systems that, together with fuzzy control methods, allow p...
Accurate quantification of soil organic matter (SOM) is crucial for improving soil fertility and maintaining ecosystem health. The content of SOM affects soil nutrient availability and is closely linked to the global carbon cycle. The use of an elect...
The artificial young forest is an important component of ecosystems, and biomass models are important for estimating the carbon storage of ecosystems. However, research on biomass models of the young forest is lacking. In this study, biomass data of...
Here, we propose a computational approach to explore evolutionary fitness in complex biological systems based on empirical data using artificial neural networks. The essence of our approach is the following. We first introduce a ranking order of inhe...
The ecotone zone, located between the Cerrado and Amazon biomes, has been under intensive anthropogenic pressures due to the expansion of commodity agriculture and extensive cattle ranching. This has led to habitat loss, reducing biodiversity, deplet...
This study explores the development and implementation of an intelligent incident management system leveraging artificial intelligence (AI), knowledge engineering, and mathematical modeling to optimize enterprise operations. Enterprise incident resol...
Intelligent transportation systems increasingly rely on artificial intelligence and predictive analytics to achieve sustainability. This study presents Adaptive Weighting, Chaos Theory, and Gaussian Mutation-based RIME algorithm-tuned Extreme Gradien...
Hybrid satellite–terrestrial network access is gaining significant attention in the 5G ecosystem and is predicted to be an essential part of future 6G standards. Multipath support is required to utilize hybrid access features that are summarize...
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