To improve the optimization performance of LSHADE algorithm, an alternative adaptation approach for selection control parameters is proposed. The proposed named LSHADE-SPA, uses a new semi-parameter to effectively adapt values scaling factor Differential evolution algorithm. consists two different settings F and Cr. benefit this prove that semi-adaptive algorithm better than pure random or fully adaptive self-adaptive enhance our we also introduced hybridization framework LSHADE-SPACMA...

This paper introduces an enhancement of the recent developed Gaining Sharing Knowledge based algorithm, dubbed as GSK. algorithm is excellent example a contemporary nature-based which inspired from human life behavior gaining and sharing knowledge to solve optimization task. GSK simulates natural phenomena using two main phases: junior senior. A set initial solutions are generated at beginning search consideredjuniors. Later, individuals moving senior stage by interacting with environment...

The initiative to introduce new benchmark problems has drawn attention the development of optimization algorithms. Recently, a set constrained been developed as addition CEC series. This paper proposed hybrid variant gaining sharing knowledge based algorithm with adaptive parameters and improved multi-operator differential evolution (IMODE) algorithm, called APGSK-IMODE. It enhanced performance recently algorithm. APGSK-IMODE tested on CEC2021 which contains 10 test functions dimensions 20....

Individual abnormal behaviors vary depending on crowd sizes, contexts, and scenes. Challenges such as partial occlusions, blurring, a large number of behaviors, camera viewing occur in large-scale crowds when detecting, tracking, recognizing individuals with abnormalities. In this paper, our contribution is two-fold. First, we introduce an annotated labeled behavior Hajj dataset, HAJJv2. Second, propose two methods hybrid convolutional neural networks (CNNs) random forests (RFs) to detect...

In equestrian sports and veterinary medicine, horse welfare is paramount. Horse tiredness, lameness, colic, anemia can be identified classified using deep learning (DL) models. These technologies analyze images videos to help vets researchers find symptoms trends that are hard see. Early detection better treatment of certain disorders improve horses’ health. DL models also with new data, improving diagnosis accuracy efficiency. This study comprehensively evaluates three convolutional neural...

During the last decade, large-scale global optimization has been one of active research fields. Optimization algorithms are affected by curse dimensionality associated with this kind complex problems. To solve problem, a new memetic framework for solving problems is proposed in paper. In framework, success history-based differential evolution linear population size reduction and semi-parameter adaptation (LSHADE-SPA) used exploration, while modified version multiple trajectory search local...

During last two decades, Differential Evolution (DE) proved to be one of the most popular and successful evolutionary algorithms for solving global optimization problems over continuous space. Proposing new mutation strategies improve performance is considered a significant research study. In DE, operation plays vital role in algorithm. Therefore, this paper, comprehensive analysis contributions on basic novel that were proposed between 1995 2020 presented. A taxonomy based structure...

Abstract To develop new meta-heuristic algorithms and evaluate on the benchmark functions is most challenging task. In this paper, performance of various developed are evaluated recently CEC 2021 functions. The objective parametrized by inclusion operators, such as bias, shift rotation. different combinations binary operators applied to which leads CEC2021 Therefore, considered solve with dimensions. some basic, advanced meta-heuristics that participated in competition have been...

As optimization algorithms have a great power to solve nonlinear, complex, and hard problems, nature-inspired been applied extensively in distinct fields order real life cases. In this paper, modifications for the recently proposed Gaining-Sharing-Knowledge based algorithm (GSK) are presented enhancing its performance. is considered as perfect example of modern that human behavior source inspiration problems. GSK mimics naturalistic phenomenon gaining knowledge sharing back being through two...

The effort devoted in introducing new numerical optimization benchmarks has attracted the attention to develop algorithms solve them. Very recently, a suite on bound constrained problems is proposed as addition CEC benchmark series. Differential Evolution (DE) simple Evolutionary Algorithm (EA) which shows superior performance many during past years. This paper presents extension DE algorithm through extending line of research for AGDE algorithm. algorithm, we name GADE, enhanced by...

Existing networks deemed as complex system merged with many wireless communication networks. Traditional routing algorithm may not be sufficient to meet such data transmission from the source nodes sink nodes. Therefore, serious studying and investigation for traffic performance congestion over seem an urgent challenge. Data propagation without adopting a finest techniques might lead more network or deterioration in worst case. Shortest path (SP) method has been widely used its simplicity...

Individual abnormal behaviors vary depending on crowd sizes, contexts, and scenes. Challenges such as partial occlusions, blurring, large-number behavior, camera viewing occur in large-scale crowds when detecting, tracking, recognizing individuals with behaviors. In this paper, our contribution is twofold. First, we introduce an annotated labeled Hajj dataset (HAJJv2). Second, propose two methods of hybrid Convolutional Neural Networks (CNNs) Random Forests (RFs) to detect recognize...

Performance of real-parameter global optimization algorithms is typically evaluated using sets test problems. We propose a new methodology extending these benchmarks to obtain more balanced experimental design. This can be done by selectively removing some the transformations originally used in definitions problems such as rotation, scaling, or translation. In this way, we several variants each problem parametrized interpretable, high-level characteristics. These binary parameters are...

Location-based services are one of the fastest growing technologies. Millions users using these and sharing their locations smart devices. The popularity such applications, while enabling others to access user’s location, brings with it many privacy issues. user has ability set his location preferences manually. Many face difficulties in order proper way. One solution is use machine learning based methods predict automatically. These models suffer from degraded performance when there no...

COVID-19 is a serious infection that cause severe injuries and deaths worldwide. The virus can infect people of all ages, especially the elderly. Furthermore, elderly who have co-morbid conditions (e.g., chronic conditions) are at an increased risk death. At present time, no approach exists facilitate characterization patterns In this study, to identify COVID- 19 death efficiently systematically applied by adapting Apriori algorithm. Validation evaluation proposed based on robust reliable...