We investigated the process of unsupervised generative learning and the structure of informative generative representations of images of handwritten digits (MNIST dataset). Learning models with the architecture of spa...
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The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)netw...
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The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing ***’s why a network intrusion detection system(NIDS)is needed to guard against routing assaults on RPL-based IoT *** imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network ***,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LSH-SMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization *** prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDS for three cases,namely,detection without dataset balancing,detection with SMOTE balancing,and detection with the proposed optimized LSHSOMTE *** results showed that the proposed approach outperforms the other approaches and could boost the detection *** addition,a statistical analysis is performed to study the significance and stability of the proposed *** conducted experiments include seven different types of attack cases in the RPL-NIDS17 *** on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).
The number of annual scientific publications is growing year by year, which has led to the accumulation and formation of large databases. This increases the complexity of the search for relevant articles. Modern searc...
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In terms of security and privacy,mobile ad-hoc network(MANET)continues to be in demand for additional debate and *** more MANET applications become data-oriented,implementing a secure and reliable data transfer protoc...
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In terms of security and privacy,mobile ad-hoc network(MANET)continues to be in demand for additional debate and *** more MANET applications become data-oriented,implementing a secure and reliable data transfer protocol becomes a major concern in the ***,MANET’s lack of infrastructure,unpredictable topology,and restricted resources,as well as the lack of a previously permitted trust relationship among connected nodes,contribute to the attack detection burden.A novel detection approach is presented in this paper to classify passive and active black-hole *** proposed approach is based on the dipper throated optimization(DTO)algorithm,which presents a plausible path out of multiple paths for statistics transmission to boost MANETs’quality of service.A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron(DTO-MLP),and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical(LEACH)clustering *** is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights ofminor *** hybridmethod is primarily designed to combat active black-hole *** the LEACH clustering phase,however,can also detect passive black-hole *** effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested *** diverse mobility situations,the results demonstrate up to 97%detection accuracy and faster execution ***,the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.
The theory of intuitionistic fuzzy sets (IFSs) plays an essential role to deal with uncertainty and ambiguity. However, the IFSs deal only with anticipation, not periodicity. But, complex IFSs (CIFS) can handle both u...
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Over the past decade,the power conversion efficiency of halide perovskite solar cells has shown a rapid increase to 26.1%.The significant efficiency growth and the relative simplification of the technology for o...
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Over the past decade,the power conversion efficiency of halide perovskite solar cells has shown a rapid increase to 26.1%.The significant efficiency growth and the relative simplification of the technology for obtaining thin-film solar cells due to liquid printing methods determine the high potential for the low-cost perovskite solar cells ***,efficient use of cell geometry is comparable to the size of standard crystalline-Si wafers(156:156 mm and more).Therefore,modular geometry similar to amorphous-Si solar cell approaches is used to scale perovskite solar *** electrical connection of thin-film cells requires precise processing of the conductive layers that form the device p-i-n *** subject of research is the development of a full pulsed laser scribing cycle for inverted perovskite solar *** this work,we propose a study of a laser-patterning technology In_(2)O_(3):SnO_(2)(ITO)conductive layer and a photoactive perovskite layer Cs0,2(CH(NH_(2))_(2))_(0,8)PbI_(3).Process regimes of transparent conducting electrodes based on ITO and halide perovskite layer Cs_(0,2)(CH(NH_(2))_(2))_(0,8)PbI_(3)laser patterning were *** optimal parameters for the multipass mode processing of ITO and perovskite layer were *** cell was electrically isolated at a scribe line width of 30μm.
Selecting the most relevant subset of features from a dataset is a vital step in data mining and machine *** feature in a dataset has 2n possible subsets,making it challenging to select the optimum collection of featu...
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Selecting the most relevant subset of features from a dataset is a vital step in data mining and machine *** feature in a dataset has 2n possible subsets,making it challenging to select the optimum collection of features using typical *** a result,a new metaheuristicsbased feature selection method based on the dipper-throated and grey-wolf optimization(DTO-GW)algorithms has been developed in this *** can result when the selection of features is subject to metaheuristics,which can lead to a wide range of ***,we adopted hybrid optimization in our method of optimizing,which allowed us to better balance exploration and harvesting chores more *** propose utilizing the binary DTO-GW search approach we previously devised for selecting the optimal subset of *** the proposed method,the number of features selected is minimized,while classification accuracy is *** test the proposed method’s performance against eleven other state-of-theart approaches,eight datasets from the UCI repository were used,such as binary grey wolf search(bGWO),binary hybrid grey wolf,and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hysteresis optimization(bHy),and binary hysteresis optimization(bHWO).The suggested method is superior 4532 CMC,2023,vol.74,no.2 and successful in handling the problem of feature selection,according to the results of the experiments.
The problem of the rational use of energy resources remains constantly relevant and requires the search for new approaches. One of them is power control. In AC circuits, the authors see the most promising method of ph...
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For several years, traffic congestion has been a major problem in big cities where the number of cars and different means of transportation has been increasing significantly. The problem of congestion is becoming more...
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The paper is devoted to the development of a genetic algorithm for finding the optimal values of control parameters of the ethylene oligomerization process. The formulation of the problem of optimal control of the eth...
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ISBN:
(数字)9798350349818
ISBN:
(纸本)9798350349825
The paper is devoted to the development of a genetic algorithm for finding the optimal values of control parameters of the ethylene oligomerization process. The formulation of the problem of optimal control of the ethylene oligomerization process is given. The control parameters are temperature and reaction duration, the values of which are subject to constraints. It is proposed to search for the solution of the formulated problems using a genetic algorithm with real coding. The principle of operation of genetic algorithms is based on the imitation of the processes of evolution of living nature. It includes cyclic application of selection, crossing, mutation and renewal operations to a population of individuals. For each of the problems under consideration the method of representation of the mathematical analog of the population, on the basis of which the solution is searched, is described. A step-by-step genetic algorithm for solving the formulated optimal control problems is given. A computational experiment is carried out, as a result of which the optimal reaction temperature and process duration, at which the target functional takes the largest value, are calculated.
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