Hossam M. Zawbaa

• PhD
• Professor (Assistant) at Beni-Suef University

In this paper, a variant of gray wolf optimization (GWO) that uses reinforcement learning principles combined with neural networks to enhance the performance is proposed. The aim is to overcome, by reinforced learning, the common challenge of setting the right parameters for the algorithm. In GWO, a single parameter is used to control the explorati...

Poly-lactide-co-glycolide (PLGA) is a copolymer of lactic and glycolic acid. Drug release from PLGA microspheres depends not only on polymer properties but also on drug type, particle size, morphology of microspheres, release conditions, etc. Selecting a subset of relevant properties for PLGA is a challenging machine learning task as there are over...

In this work, a novel binary version of the grey wolf optimization (GWO) is proposed and used to select optimal feature subset for classification purposes. Grey wolf optimizer (GWO) is one of the latest bio-inspired optimization techniques, which simulate the hunting process of grey wolves in nature. The binary version introduced here is performed...

Background: Selecting a subset of relevant properties from a large set of features that describe a dataset is a challenging machine learning task. In biology, for instance, the advances in the available technologies enable the generation of a very large number of biomarkers that describe the data. Choosing the more informative markers along with p...

Exploration and exploitation are two essential components for any optimization algorithm. Much exploration leads to oscillation and premature convergence while too much exploitation slows down the optimization algorithm and the optimizer may be stuck in local minima. Therefore, balancing the rates of exploration and exploitation at the optimization...

Insider threats pose a significant challenge to IT security, particularly with the rise of generative AI technologies, which can create convincing fake user profiles and mimic legitimate behaviors. Traditional intrusion detection systems struggle to differentiate between real and AI-generated activities, creating vulnerabilities in detecting malici...

Optimal power flow (OPF) problem solution is a crucial task for the operators and decision makers to assign the best setting of the system components to obtain the most economic, environmental, and technical suitable state. Artificial Hummingbird Algorithm is a recent optimization algorithm that has been applied to solving several optimization prob...

Detecting out-of-scope user utterances is essential for task-oriented dialogues and intent classification. Current methodologies face difficulties with the unpredictable distribution of outliers and often rely on assumptions about data distributions. We present the Dual Encoder for Threshold-Based Re-Classification (DETER) to address these challeng...

Wind power systems (WPs) are complex non‐linear systems with varying parameters affected by environmental changes, including wind speed fluctuations. Extracting maximum power from WPs poses a significant challenge due to these factors. Direct power control (DPC) is a highly effective technique known for its simplicity and ease of implementation. Ho...

Pupil dynamics are the important characteristics of face spoofing detection. The face recognition system is one of the most used biometrics for authenticating individual identity. The main threats to the facial recognition system are different types of presentation attacks like print attacks, 3D mask attacks, replay attacks, etc. The proposed model...

This research provides an adaptive control design in a photovoltaic system (PV) for maximum power point tracking (MPPT). In the PV system, MPPT strategies are used to deliver the maximum available power to the load under solar radiation and atmospheric temperature changes. This article presents a new adaptive control framework to enhance the perfor...

The voltage source converter (VSC) based HVDC (high voltage direct current system) offers the possibility to integrate other renewable energy sources (RES) into the electrical grid, and allows power flow reversal capability. These appealing features of VSC technology led to the further development of multi-terminal direct current (MTDC) systems. MT...

This paper studies the problem of the energy system optimization for photovoltaic (PV) generator supplying the electric vehicle. The used photovoltaic generator was conceived around a high- efficiency triple-junction solar cell InGaP/InGaAs/Ge. To adopt the photovoltaic generator to the load and to track the maximum power points, a DC-DC converter...

Metaheuristics in recent years has proven its effectiveness; however, robust algorithms that can solve real-world problems are always needed. In this paper, we suggest the first extended version of the recently introduced gaining–sharing knowledge optimization (GSK) algorithm, named multiobjective gaining–sharing knowledge optimization (MOGSK), to...

The electrical power industry has experienced an unprecedented pace of digital transformation as a prevailing economic trend in recent years. This shift towards digitalization has resulted in an increasing interest in the collection of real-time equipment condition data, which provides opportunities for implementing sensor-driven condition-based re...

This paper proposes an improved version of the Hunter-prey optimization (HPO) method to enhance its search capabilities for solving the Optimal Power Flow (OPF) problem, which includes FACTS devices and wind power energy integration. The new algorithm is inspired by the behavior of predator and prey animals, such as lions, wolves, leopards, stags,...

Protein structure prediction is one of the important aspects while dealing with critical diseases. An early prediction of protein folding helps in clinical diagnosis. In recent years, applications of metaheuristic algorithms have been substantially increased due to the fact that this problem is computationally complex and time-consuming. Metaheuris...

Today, the importance of enhanced quality of service and energy optimization has promoted research into sensor applications such as pervasive health monitoring, distributed computing, etc. In general, the resulting sensor data are stored on the cloud server for future processing. For this purpose, recently, the use of fog computing from a real-worl...

Water is a precious resource for agriculture and most of the land is irrigated by tube wells. Diesel engines and electricity-operated pumps are widely used to fulfill irrigation water requirements; such conventional systems are inefficient and costly. With rising concerns about global warming, it is important to choose renewable energy source. In t...

The JAYA is classified as the state-of-the-art population-oriented algorithm for the optimization of diverse problems, both discrete and continuous. The concept behind this algorithm is to present a solution by means of the best and worst individuals in the population. On the other hand, teaching–learning-based optimization algorithm cooperation of...

The droop mechanism is widely utilized in a stand‐alone microgrid (MG) to regulate power‐sharing among distributed generators (DG). However, over the years, the droop phenomena are continually modified to lessen the deviation in voltage and frequency parameters caused due to classical droop. This study suggests computing the droop coefficient for v...

In recent years, various deep neural networks with different learning paradigms have been widely employed in various applications, including medical diagnosis, image analysis, self-driving vehicles and others. The activation functions employed in deep neural networks have a huge impact on the training model and the reliability of the model. The Rec...

This work discusses the production of a novel hybrid algorithm by combining the gorilla troops optimizer (GTO) with the gradient-based optimizers (GBO) approach. The novel approach is called GTO-GBO, it is offered as a useful tool for optimizing the power system stabilizer (PSS) used in the IEEE four-generator, two-area multi-machine power system s...

One of the main causes of CO2 emissions is the production of electrical energy. Therefore, many researchers goal’s is to develop renewable power systems. This paper proposes a new intelligent control development of hybrid PV-Wind-Batteries. Neuro-Fuzzy Direct Power Control (NF-DPC) is invested in order to enhance system performance and generated cu...

In current days, sensor nodes are deployed in hostile environments for various military and commercial applications. Sensor nodes are becoming faulty and having adverse effects on the network if they are not diagnosed and informed of the fault status to other nodes. Fault diagnosis is difficult when the nodes behave at fault sometimes and provide g...

Smart control tactics, wider stability region, rapid reaction time, and high-speed performance are essential requirements for any controller to provide a smooth, vibrationless, and efficient performance of an in-house fabricated active magnetic bearing (AMB) system. In this manuscript, three pre-eminent population-based metaheuristic optimization t...

One of the most complex areas of image processing is image classification, which is heavily relied upon in clinical care and educational activities. However, conventional models have reached their limits in effectiveness and require extensive time and effort to extract and choose classification variables. In addition, the large volume of medical im...

This paper presents an application of new developed meta-heuristic Geometric Mean Optimization (GMO) algorithm, which mimics geometric mean operator unique features in mathematics with combination of power loss sensitivity index (PLSI) for the problem of optimal network reconfiguration (NR), optimal distributed generation (DG) unit allocation with...

This article offers a flatness theory-based energy management strategy (FEMS) for a hybrid power system consisting of a supercapacitor (SC) and lithium-ion battery. The proposed FEMS intends to allocate the power reference for the DC/DC converters of both the battery and SC while attaining higher efficiency and stable DC bus voltage. First, the ent...

In this paper, a new isolated hybrid system is simulated and analyzed to obtain the optimal sizing and meet the electricity demand with cost improvement for servicing a small remote area with a peak load of 420 kW. The major configuration of this hybrid system is Photovoltaic (PV) modules, Biomass gasifier (BG), Electrolyzer units, Hydrogen Tank un...

The insulating material is made from rice husk and epoxy resin which are ecologically friendly and incredibly durable. When coarse Rice husk is mechanically disintegrated, fibrils are formed. By weaving together fibrillated threads, and robust biodegradables, lightweight dielectric fibers are created. Then the Composites are examined utilizing a bl...

Nowadays, load serving entities require more active participation from consumers. In this context, demand response programs and home energy management systems play a crucial role in achieving multiple goals such as peak clipping. However, the adoption of demand response initiatives typically has a negative impact on the monetary expenditures of the...

The shift of transportation technology from internal combustion engine (ICE) based vehicles to electric vehicles (EVs) in recent times due to their lower emissions, fuel costs, and greater efficiency has brought EV technology to the forefront of the electric power distribution systems due to their ability to interact with the grid through vehicle-t...

This paper introduces a novel technique for optimal distribution system (DS) planning with distributed generation (DG) systems. It is being done to see how active and reactive power injections affect the system’s voltage profile and energy losses. DG penetration in the power systems is one approach that has several advantages such as peak savings,...

The actual energetic situation has several challenges such as pollution, the rarefaction of fossil fuel and the dangers of nuclear. Renewable sources are proposed as a solution and suggested, such as a cost-effectiveness system. The paper deals with the problem of feeding a domestic load with electricity which should respect the ecologies factors,...

The use of diesel engines has increased dramatically in recent years, as has the number of exhaust emissions. These emissions have the potential to endanger Mother Nature and the living species within it. Governments all over the world have introduced legislative rules on exhaust emission reduction in order to limit the number of emissions released...

One of the most critical operations aspects is power management strategies for hybrid AC/DC microgrids. This work presented power management in hybrid AC–DC microgrids with a droop control strategy. At first, photovoltaic, Wind, and battery are used as the power sources, which supply the power with uncertainties. The AC and DC microgrids are contro...

The current paper explores the influence of disintegrated energy and economic complexity on CO2 emissions (CO2) in the top economic complexity economies. The model also incorporates other drivers of CO2, such as technological innovation and economic growth. The current research utilizes data stretching from 1993 to 2018. The research employed Weste...

Thermo-hydraulic performance of a Double Pass Parallel Flow Solar Air Heater (DPPFSAH) roughened with perforated multi-V ribs have been studied experimentally in a prior study and the effect of variation in open area ratio and change in relative roughness width has been analysed and reported. The current work builds upon the aforementioned earlier...

Cryogenic Treatment is one of the heat treatment processes, which is used to develop the wear resistance property of tool material and remove residual stresses in Tool steels for better machining performance. This paper focuses on cryogenically treated T42 tool performance on mild steel as workpiece material. For investigating the machining perform...

The current paper assessed the time-frequency analysis interrelationship between CO2 emissions and financial development, economic growth, renewable energy use, structural change, and non-renewable energy use in Sweden. We utilized a quarterly dataset stretching from 1980-2019. In order to unlock these interrelationships, we leverage wavelet tools...

Electrical power system abnormalities may have several negative consequences on its stable operation. As a result, preserving its stability under such operational states has become an ongoing challenge for power engineers. PSSs are created as auxiliary controllers to address the instability issues produced upon disturbances. They dampen the oscilla...

Manta ray foraging optimization (MRFO) algorithm is relatively a novel bio-inspired optimization technique directed to given real-world engineering problems. In this present work, wind turbines layout (WTs) inside a wind farm is considered a real nonlinear optimization problem. In spite of the better convergence of MRFO, it gets stuck into local op...

The thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show...

Most of the loads used in our day-to-day life are non-linear in nature. To investigate the performance of various non-linear loads, a laboratory setup on different load combinations such as light, fan and drive system in this work. The unbalance in supply voltages, supply current and frequency, reduction in power factor and total harmonic distortio...

The permanent magnet synchronous motor (PMSM) has several advantages over the DC motor and is gradually replacing it in the industry. The dynamics of the PMSM are described by non-linear equations; it is sensitive to unknown external disturbances (load), and its characteristics vary over time. All of these restrictions complicate the control task....

The demonstrated research work analyses the technoeconomic modelling and sensitivity analysis of the available resources for the rural community in India. The various resources used in this study are solar, wind, hydro, battery and utility grid connected system. The usefulness of the on grid system in rural sector is that excess amount of electrici...

The residential load sector plays a vital role in terms of its impact on overall power balance, stability, and efficient power management. However, the load dynamics of the energy demand of residential users are always nonlinear, uncontrollable, and inelastic concerning power grid regulation and management. The integration of distributed generation...

This paper proposes an improved version of Barnacles mating optimizer (BMO) for solving the optimal allocation problem of distribution generator (DGs) in radial distribution systems (RDSs). BMO is a recent bioinspired optimization algorithm that mimics the intelligence behavior of Barnacles' mating. However, like with any metaheuristic optimization...

Object-based features like spectral, topographic, and textural are supportive to determine debris-covered glacier classes. The original feature space includes relevant and irrelevant features. The inclusion of all these features increases the complexity and renders the classifier’s performance. Therefore, feature space optimization is requisite for...

This work proposes an intelligent allocation of distributed generation (DG) units and shunt reactive com-pensators (SRC) with high penetration capacities into distribution systems for power loss mitigation using the Bald Eagle Search (BES) optimization algorithm. The intelligent allocation causes a reduction in voltage variations and enhances the v...

Although ICT has played a critical role in the socio-economic growth of human cultures, it has also brought with it significant environmental risks. Nevertheless, scholars remain divided on this topic; some believe that ICT has had a positive influence on the quality of the environment, while others believe that ICT has created major environmental...

Drilling is the hole making process on the component face with the aid of a twisted drillbit. Normal drill bits easily wear out through penetration of drill bit into the workpiece material due to force generated in the drilling operation. So this work tries to investigate the machining parameters with cryogenically treated drill bits on various res...

The penetration of renewable energy resources into electric power networks has been increased considerably to reduce the dependence of conventional energy resources, reducing the generation cost and greenhouse emissions. The wind and photovoltaic (PV) based systems are the most applied technologies in electrical systems compared to other technologi...

Many emerging economies, including the BRICS economies, are having difficulty meeting the Sustainable Development Goals' (SDGs) objectives. Consequently, this research discusses the creation of an SDG framework for the BRICS economies, which can be utilized as a model for other blocs. To achieve this purpose, this research probes into the effect of...

Turkey is a laggard in terms of the achievement of its Sustainable Development Goals (SDGs), and one of the primary issues it faces is environmental deterioration. Therefore, a policy-level reorientation may be needed to address this relevant issue. From this standpoint, this research assesses the impact of renewable energy (RE) use and financial d...

COVID-19 had different waves within thesame country. The spread rate and severity showed different properties within the COVID-19 different waves. The present work aims to compare the spread and the severity of the different waves using the available data of confirmed COVID-19 cases and death cases. Real-datasets collected from the Johns Hopkins Un...

Renewable energy-based hybrid power systems are being increasingly deployed across the globe to reduce carbon emissions. The system frequency and tie-line power tend to fluctuate due to system operating conditions. These fluctuations can be maintained within the desired limits using optimally designed controllers. In this article, the recently deve...

Although using a series compensation technique in a long transmission line effectively increases the transmittable power; it may cause a sub-synchronous resonance (SSR) phenomenon. Gate-controlled series capacitor (GCSC) is an effective method for SSR damping by controlling the turn-off angle. In the previous studies, a constant supplementary dampi...

The power sector of developing countries is the backbone of the economy, and robust implementation of energy policies can play a significant role in its expansion. India is blessed to have ample natural resources; the only necessity is to identify these unseen resources comprehensively. India is an agricultural country with plenty of livestock gene...

The permanent magnet synchronous motor (PMSM) has several advantages over the DC motor and is gradually replacing it in the industry. The dynamics of the PMSM are described by nonlinear equations; it is sensitive to unknown external disturbances (load), and its characteristics vary over time. All of these restrictions complicate the control task. N...

Meta-heuristic algorithms have shown promising results in solving various optimization problems. The crow search algorithm (CSA) is a new and effective meta-heuristic algorithm that emulates crows’ intelligent group behavior in nature. However, it suffers from several problems, such as trapping into local optimum and premature convergence. This pap...

Backgrounds SARS-CoV-2 is affecting different countries all over the world, with significant variation in infection-rate and death-ratio. We have previously shown a presence of a possible relationship between different variables including the Bacillus Calmette–Guérin (BCG) vaccine, average age, gender, and malaria treatment, and the rate of spread,...

Coronavirus-19 (COVID-19) is the black swan of 2020. Still, the human response to restrain the virus is also creating massive ripples through different systems, such as health, economy, education, and tourism. This paper focuses on research and applying Artificial Intelligence (AI) algorithms to predict COVID-19 propaga- tion using the available ti...

Introduction Aerosol delivery from DPIs could be affected by different factors. This study aimed to evaluate and predict the effects of different factors on drug delivery from DPIs. Methods Modeling and optimization for both in-vitro and in-vivo data of different DPIs (Diskus, Turbohaler, and Aerolizer) were carried out using neural networks associ...

Harmony search (HS) is a type of population-based optimization algorithm that is introduced based on the idea of musical instruments being tuned to obtain the best harmony state. Several versions of HS have been presented, with global harmony search (GHS) considered one of the most popular. Although GHS is efficient in solving various optimization...

Herein, two new swarm intelligence based algorithms namely; grey wolf optimization (GWO) and antlion optimization (ALO) algorithms were presented, for the first time, as variable selection tools in spectroscopic data analysis. In order to assess the performance of these algorithms, they were applied along with the recently introduced firefly algori...

COVID-19 is affecting different countries all over the world with great variation in infection rate and death ratio. Some reports suggested a relation between the Bacillus Calmette-Guérin (BCG) vaccine and the malaria treatment to the prevention of SARS-CoV-2 infection. Some reports related infant's lower susceptibility to the BCG vaccine. Some oth...

In this paper, a modification of the newly proposed antlion optimization (ALO) is introduced and applied to feature selection relied on the Lèvy flights. ALO method is one of the encouraging swarm intelligence algorithms which make use of random walking to perform the exploration and exploitation operations. Random walks based on uniform distributi...

In this paper, a variant based on Lèvy flight was proposed to enhance the performance of two recently proposed optimizers. The first optimizer used in the study is Sine-Cosine Algorithm (SCA) while the second is Whale Optimization Algorithm (WOA). Both optimizers are composed of two phases of random walks in each optimization iteration and both hav...

In pharmaceutical development, it is very useful to exploit the knowledge of the causal relationship between product quality and critical material attributes (CMA) in developing new formulations and products, and optimizing manufacturing processes. With the big data captured in the pharmaceutical industry, computational intelligence (CI) models cou...

Selection of a representative set of features is still a crucial and challenging problem in machine learning. The complexity of the problem increases when any of the following situations occur: a very large number of attributes (large dimensionality); a very small number of instances or time points (small-instance set). The first situation poses pr...

This chapter presents one of the recently proposed bio-inspired optimization methods, namely, flower pollination algorithm (FPA). FPA for its capability to adaptively search a large search space with maybe many local optima has been employed to solve many real problems. FPA is used to handle the feature selection problem in wrapper-based approach w...

One of the most important tasks for variant approaches such as text categorization, voice recognition, image processing, proteins structure predictions, microarray gene expression and so on is classification. The majority of the current supervised classification techniques are based on traditional statistics, that can provide perfect results when t...

In this paper, a variant of the recently introduced whale optimization algorithm (WOA) was proposed based on adaptive switching of random walk per individual search agent. WOA is recently proposed bio-inspired optimizers that employ two different random walks. The original optimizer stochastically switches between the two random walk at each iterat...

This paper presents a multi-objective retinal blood vessels localization approach based on flower pollination search algorithm (FPSA) and pattern search (PS) algorithm. FPSA is a new evolutionary algorithm based on the flower pollination process of flowering plants. The proposed multi-objective fitness function uses the flower pollination search al...

Nowadays, there are many tools and techniques that can support management in the information security field. In order to deal with any kind of security, authentication plays an important role. In biometrics, a human being needs to be identified based on some unique personal characteristics and parameters. DNA (desoxyribonucleic acid) is the part of...

There are many tools and techniques that can support management in the information security field. In order to deal with any kind of security, authentication plays an important role. In biometrics, a human being needs to be identified based on some unique personal characteristics and parameters. In this book chapter, the researchers will present an...

In this paper, binary variants of the ant lion optimizer (ALO) are proposed and used to select the optimal feature subset for classification purposes in wrapper-mode. ALO is one of the recently bio-inspired optimization techniques that imitates the hunting process of ant lions. Moreover, ALO balances exploration and exploitation using single operat...

This implementation is based on the paper by: Emary E, Zawbaa HM (2016) Impact of chaos functions on modern swarm optimizers. PLoS ONE 11(6): e0158738, July 2016. DOI: 10.1371/journal.pone.0158738. http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0158738 All work making use of such code must cite that paper.

This implementation is based on the paper by: Emary E, Zawbaa HM (2016) Impact of chaos functions on modern swarm optimizers. PLoS ONE 11(6): e0158738, July 2016. DOI: 10.1371/journal.pone.0158738. http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0158738 All work making use of such code must cite that paper.

In this work, a proposed hybrid dragonfly algorithm (DA) with extreme learning machine (ELM) system for prediction problem is presented. ELM model is considered a promising method for data regression and classification problems. It has fast training advantage, but it always requires a huge number of nodes in the hidden layer. The usage of a large n...

Nowadays, a dataset includes a huge number of features with irrelevant and redundant ones. Feature selection is required for a better machine-learning algorithms’ performance. A system for feature selection is proposed in this work using a sine cosine algorithm (SCA). SCA is a new stochastic search algorithm for optimization problems. SCA optimizat...

Many difficulties are facing a handwritten Arabic recognition system such as unlimited variation in human handwriting, similarities of distinct character shapes, interconnections of neighboring characters and their position in a word. This paper presents a handwritten Arabic character recognition system based on BA algorithm. BA algorithm is adopte...

In this work, a feature selection algorithm based on moth-flame optimization (MFO) is proposed. Moth-flame optimization (MFO) is a recently proposed swarm intelligent optimization algorithm that mimics the motion of moths. The proposed algorithm is applied in the domain of machine learning for feature selection to find the optimal feature combinati...