A new backtracking algorithm based on matrix storage was proposed, and the realization detail of the algorithm was discussed. Further, the complexity of the algorithm was analyzed. The analysis result show the algorithm is more efficient comparing the similar method, and the application result show ...
This paper presents a novel hybrid long-term forecasting method with support vector regression(SVR) and backtracking search algorithm(BSA) optimization algorithm, which is used to obtain the parameters of the SVR. The practical case of China's annual electricity demand is used to evaluate the ...
Greedy algorithm: In this, we make a decision by considering the local (immediate) best option and assume it as a global optimal. Divide and conquer algorithm: This type of algorithm will divide the main problem into sub-problems and then would solve them individually. Backtracking algorithm: ...
To solve bankruptcy prediction tasks, we proposed an improved rime optimization technique (RMRIME). The proposed RMRIME algorithm first employs roulette wheel selection step, introducing random individuals into the position updating process to expand the search space and boost the RMRIME’s exploration ...
A Genetic Algorithm (GA) is a soft computing technique influenced by biological processes. The core concept of GA consists of two fundamental elements: individuals and populations. In this context, “population” refers to a group of individual solutions that need to be optimized. Building on this...
The participant does control their path through the world, thus a magic carpet flight simulation algorithm was necessary. A simple-but-flexible flight control system was developed that would enable most of the general population to figure out how to direct the flight of the carpet. Steering was...
backtracking search iteration reordering algorithm) were put forward.Experiments were performed on computational fluid dynamics,which was a representative irregular application.It is indicated that data locality is improved by the single reordering algorithm,with the execution speed increasing by 25.4%.The ...
Fig. 7. DAGs are used in memory to assist the backtracking of the DFS algorithm when updating the derivation subgraph. The derivation instances are treated as vertices and their connections as edges. Depending on the root derivation chosen, different DAGs can be generated. 3.2.2. Asynchronous co...
along with the introduction of a random-weighted reflection coefficient and a novel control operator. In a sequence of tests, the enhanced algorithm demonstrates a significant superiority over its competitors. Nama et al.19introduced a refined backtracking search technique known as GQR-BSA. The client...
The backtracking algorithm uses delta rules to compute a local gradient drop from the output neuron back to each neuron in the input layer. First get the error of each output neuron $$ e_{j} (n)\, = \,d_{j} (n)\, - \,o_{j} (n) $$ (2) The \( j \)-th neuron for ...