Zeshan Aslam Khan
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View article: Explainable clinical diagnosis through unexploited yet optimized fine-tuned ConvNeXt Models for accurate monkeypox disease classification
Explainable clinical diagnosis through unexploited yet optimized fine-tuned ConvNeXt Models for accurate monkeypox disease classification Open
View article: Fine-tuned deep transfer learning: an effective strategy for the accurate chronic kidney disease classification
Fine-tuned deep transfer learning: an effective strategy for the accurate chronic kidney disease classification Open
Kidney diseases are becoming an alarming concern around the globe. Premature diagnosis of kidney disease can save precious human lives by taking preventive measures. Deep learning demonstrates a substantial performance in various medical d…
View article: Design of Chaos Induced Aquila Optimizer for Parameter Estimation of Electro-Hydraulic Control System
Design of Chaos Induced Aquila Optimizer for Parameter Estimation of Electro-Hydraulic Control System Open
View article: Systematic Analysis of Latent Fingerprint Patterns through Fractionally Optimized CNN Model for Interpretable Multi-Output Identification
Systematic Analysis of Latent Fingerprint Patterns through Fractionally Optimized CNN Model for Interpretable Multi-Output Identification Open
View article: EA-CNN: Enhanced attention-CNN with explainable AI for fruit and vegetable classification
EA-CNN: Enhanced attention-CNN with explainable AI for fruit and vegetable classification Open
The quality of vegetables and fruits are judged by their visual features. Misclassification of fruits and vegetables lead to a financial loss. To prevent the loss, superstores need to classify fruits and vegetables in terms of size, color …
View article: Fractional gradient optimized explainable convolutional neural network for Alzheimer's disease diagnosis
Fractional gradient optimized explainable convolutional neural network for Alzheimer's disease diagnosis Open
View article: Knacks of marine predator heuristics for distributed energy source-based power systems harmonics estimation
Knacks of marine predator heuristics for distributed energy source-based power systems harmonics estimation Open
View article: Knacks of Evolutionary Mating Heuristics for Renewable Energy Source–Based Power Systems Signal Harmonics Estimation
Knacks of Evolutionary Mating Heuristics for Renewable Energy Source–Based Power Systems Signal Harmonics Estimation Open
Renewable energy sources–based power systems are increasing rapidly every year with higher chances of destabilization and low power quality due to harmonics, subharmonics, and interharmonics. The elimination of the root causes of these har…
View article: Design of Nonlinear Marine Predator Heuristics for Hammerstein Autoregressive Exogenous System Identification with Key-Term Separation
Design of Nonlinear Marine Predator Heuristics for Hammerstein Autoregressive Exogenous System Identification with Key-Term Separation Open
Swarm-based metaheuristics have shown significant progress in solving different complex optimization problems, including the parameter identification of linear, as well as nonlinear, systems. Nonlinear systems are inherently stiff and diff…
View article: Variants of Chaotic Grey Wolf Heuristic for Robust Identification of Control Autoregressive Model
Variants of Chaotic Grey Wolf Heuristic for Robust Identification of Control Autoregressive Model Open
In this article, a chaotic computing paradigm is investigated for the parameter estimation of the autoregressive exogenous (ARX) model by exploiting the optimization knacks of an improved chaotic grey wolf optimizer (ICGWO). The identifica…
View article: Design of Confidence-Integrated Denoising Auto-Encoder for Personalized Top-N Recommender Systems
Design of Confidence-Integrated Denoising Auto-Encoder for Personalized Top-N Recommender Systems Open
A recommender system not only “gains users’ confidence” but also helps them in other ways, such as reducing their time spent and effort. To gain users’ confidence, one of the main goals of recommender systems in an e-commerce industry is t…
View article: Novel FDIs-based data manipulation and its detection in smart meters’ electricity theft scenarios
Novel FDIs-based data manipulation and its detection in smart meters’ electricity theft scenarios Open
Non-technical loss is a serious issue around the globe. Consumers manipulate their smart meter (SM) data to under-report their readings for financial benefit. Various manipulation techniques are used. This paper highlights novel false data…
View article: Enhanced fractional adaptive processing paradigm for power signal estimation
Enhanced fractional adaptive processing paradigm for power signal estimation Open
Fractional calculus tools have been exploited to effectively model variety of engineering, physics and applied sciences problems. The concept of fractional derivative has been incorporated in the optimization process of least mean square (…
View article: Parameter estimation of harmonics arising in electrical instruments of smart grids using cuckoo search heuristics
Parameter estimation of harmonics arising in electrical instruments of smart grids using cuckoo search heuristics Open
The accurate estimation of power signal parameters allows smart grids to optimize power delivery efficiency, improve equipment utilization, and control power flow among generation nodes and loads. However, practically it becomes a challeng…
View article: Nonlinear Hammerstein System Identification: A Novel Application of Marine Predator Optimization Using the Key Term Separation Technique
Nonlinear Hammerstein System Identification: A Novel Application of Marine Predator Optimization Using the Key Term Separation Technique Open
The mathematical modelling and optimization of nonlinear problems arising in diversified engineering applications is an area of great interest. The Hammerstein structure is widely used in the modelling of various nonlinear processes found …
View article: Dwarf Mongoose Optimization Metaheuristics for Autoregressive Exogenous Model Identification
Dwarf Mongoose Optimization Metaheuristics for Autoregressive Exogenous Model Identification Open
Nature-inspired metaheuristic algorithms have gained great attention over the last decade due to their potential for finding optimal solutions to different optimization problems. In this study, a metaheuristic based on the dwarf mongoose o…
View article: Electricity Theft Detection in Smart Grids Using a Hybrid BiGRU–BiLSTM Model with Feature Engineering-Based Preprocessing
Electricity Theft Detection in Smart Grids Using a Hybrid BiGRU–BiLSTM Model with Feature Engineering-Based Preprocessing Open
In this paper, a defused decision boundary which renders misclassification issues due to the presence of cross-pairs is investigated. Cross-pairs retain cumulative attributes of both classes and misguide the classifier due to the defused d…
View article: Design of Aquila Optimization Heuristic for Identification of Control Autoregressive Systems
Design of Aquila Optimization Heuristic for Identification of Control Autoregressive Systems Open
Swarm intelligence-based metaheuristic algorithms have attracted the attention of the research community and have been exploited for effectively solving different optimization problems of engineering, science, and technology. This paper co…
View article: Hierarchical Quasi-Fractional Gradient Descent Method for Parameter Estimation of Nonlinear ARX Systems Using Key Term Separation Principle
Hierarchical Quasi-Fractional Gradient Descent Method for Parameter Estimation of Nonlinear ARX Systems Using Key Term Separation Principle Open
Recently, a quasi-fractional order gradient descent (QFGD) algorithm was proposed and successfully applied to solve system identification problem. The QFGD suffers from the overparameterization problem and results in estimating the redunda…
View article: Maximum-Likelihood-Based Adaptive and Intelligent Computing for Nonlinear System Identification
Maximum-Likelihood-Based Adaptive and Intelligent Computing for Nonlinear System Identification Open
Most real-time systems are nonlinear in nature, and their optimization is very difficult due to inherit stiffness and complex system representation. The computational intelligent algorithms of evolutionary computing paradigm (ECP) effectiv…
View article: Flower Pollination Heuristics for Nonlinear Active Noise Control Systems
Flower Pollination Heuristics for Nonlinear Active Noise Control Systems Open
In this paper, a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems. The recently introduced flower pollination based heuristics is implemented to minim…
View article: A New Users Rating-Trend Based Collaborative Denoising Auto-Encoder for Top-N Recommender Systems
A New Users Rating-Trend Based Collaborative Denoising Auto-Encoder for Top-N Recommender Systems Open
To promote online businesses and sales, e-commerce industry focuses to fulfill users' demands by giving them top set of recommendations which are ranked through different ranking measures.Deep learning based auto-encoder models have furthe…