Search Results - (( mobile evaluation bat algorithm ) OR ( _ classification modified algorithm ))

Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm by ,, Dwi Pebrianti, Ann Ayop azmi, Nurnajmi Qasrina, Bayuaji, Luhur, Suarin, Nur Aisyah Syafinaz, ,, Muhammad Syafrullah

Get full text
Get full text

Performance evaluation of PID controller parameters gain optimization for wheel mobile robot based on bat algorithm and particle swarm optimization by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Nurnajmin Qasrina, Ann, Bayuaji, Luhur, Syafrullah, Muhammad, Riyanto, Indra

Get full text
Get full text
Get full text
Get full text

Performance evaluation of PID controller parameters gain optimization for wheel mobile robot based on bat algorithm and particle swarm optimization by Nur Aisyah Syafinaz, Suarin, Pebrianti, Dwi, Nurnajmin Qasrina, Ann, Luhur, Bayuaji, Muhammad, Syafrullah, Indra, Riyanto

Get full text
Get full text
Get full text
Get full text

A comprehensive overview of classical and modern route planning algorithms for self-driving mobile robots by Wan Daud, Wan Mohd Bukhari, Abu, Nur Syuhadah, Omar, Siti Nashayu, Sohaimeh, Shahirul Ashraf, Adli,, M. H.

“…Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. …”
Get full text
Get full text
Get full text

Bat optimized link state routing protocol for energy-aware mobile ad-hoc networks by Jubair M.A., Mostafa S.A., Muniyandi R.C., Mahdin H., Mustapha A., Hassan M.H., Mahmoud M.A., Al-Jawhar Y.A., Al-Khaleefa A.S., Mahmood A.J.

“…The symmetry between OLSR of MANET and Bat Algorithm (BA) is that both of them use the same mechanism for finding the path via sending and receiving specific signals. …”

Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

“…Both Bat Algorithm parameters and AFW parameters are adaptively tuned to balance exploration and exploitation throughout the optimization process. …”
Get full text
Get full text
Get full text

The use of SOM for fingerprint classification by Turky A.M., Ahmad M.S.

Subjects:

A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

“…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
Get full text
Get full text
Get full text

A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

“…The first stage consists of a modified fuzzy min-max (FMM) neural-network-based pattern classifier, while the second stage consists of a genetic-algorithm (GA)-based rule extractor. …”
Get full text

Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…In addition, a contextual text classification experiment is conducted using benchmarked datasets to assess the performance of the modified word vectors in the targeted classification task. …”
Get full text
Get full text
Get full text

A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

“…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
Get full text
Get full text

Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

“…This work proposed the implementation of modified Artificial Bee Colony with Firefly algorithm for training the FLNN network to overcome the drawback of BP-learning algorithm. …”
Get full text
Get full text
Get full text
Get full text

Improved swarm intelligence algorithms with time-varying modified Sigmoid transfer function for Amphetamine-type stimulants drug classification by Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri, Carbo-Dorca, Ramon, Abraham, Ajith

“…The new binary algorithms, BPSO, BGWOA, BWOA, BHHO, and BMRFO algorithms are utilized for solving the descriptors selection problem in supervised Amphetamine-type Stimulants (ATS) drug classification task. …”
Get full text
Get full text
Get full text

Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

“…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
Get full text
Get full text

An approach to improve functional link neural network training using modified artificial bee colony for classification task by Yana Mazwin Mohmad Hassim, Rozaida Ghazali

“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
Get full text
Get full text
Get full text

An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
Get full text
Get full text

An approach to improve functional link neural network training using modified artificial bee colony for classification task by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. Still, BP-learning algorithm has difficulties such as trapping in local optima and slow convergence especially for solving non-linearly separable classification problems. …”
Get full text
Get full text

An Improved Wavelet Neural Network For Classification And Function Approximation by Ong , Pauline

“…The modified WNN was then applied in the areas of classification and function approximation.…”
Get full text
Get full text

Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

“…The results show that the proposed modified ANFIS architecture with gaussian membership function and Artificial Bee Colony (ABC) optimization algorithm, on average has achieved classification accuracy of 99.5% with 83% less computational complexity.…”
Get full text
Get full text
Get full text
Get full text

The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

“…However, none of the available works had proposed BFOA as a classification algorithm despite of its good performance. …”
Get full text
Get full text
Get full text